Eye movements across viewpoint changes in multiple object tracking

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Eye movements across viewpoint changes in multiple object trackingMarkus Huffa; Frank Papenmeiera; Georg Jahnb; Friedrich W. Hessea

a Knowledge Media Research Center, Tübingen, Germany b Department of Psychology, University ofGreifswald, Greifswald, Germany

First published on: 01 September 2010

To cite this Article Huff, Markus , Papenmeier, Frank , Jahn, Georg and Hesse, Friedrich W.(2010) 'Eye movements acrossviewpoint changes in multiple object tracking', Visual Cognition, 18: 9, 1368 — 1391, First published on: 01 September2010 (iFirst)To link to this Article: DOI: 10.1080/13506285.2010.495878URL: http://dx.doi.org/10.1080/13506285.2010.495878

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Eye movements across viewpoint changes in multiple

object tracking

Markus Huff and Frank Papenmeier

Knowledge Media Research Center, Tubingen, Germany

Georg Jahn

Department of Psychology, University of Greifswald, Greifswald, Germany

Friedrich W. Hesse

Knowledge Media Research Center, Tubingen, Germany

Observers can visually track multiple objects that move independently even if thescene containing the moving objects is rotated in a smooth way. Abrupt scene rota-tions yield tracking more difficult but not impossible. For nonrotated, stable dy-namic displays, the strategy of looking at the targets’ centroid has been shown to beof importance for visual tracking. But which factors determine successful visualtracking in a nonstable dynamic display? We report two eye tracking experimentsthat present evidence for centroid looking. Across abrupt viewpoint changes, gazeon the centroid is more stable than gaze on targets indicating a process of realigningtargets as a group. Further, we show that the relative importance of centroid look-ing increases with object speed.

Keywords: Attention; Eye movements; Multiple object tracking; Visual cognition.

Watching and understanding a football game on television requires the

ability to keep track of multiple moving objects: For example, in a scene in

front of the goal, at least two players (offence and goal-keeper) and the ball

have to be tracked. More complex situations (e.g., an off-side position)

involve even more players. In contrast to real life scenarios, in television

a tactic move (e.g., a counterattack) is often shown in sequential shots from

Please address all correspondence to Markus Huff, Knowledge Media Research Centre,

Konrad-Adenauer-Str. 40, D-72072 Tubingen, Germany. E-mail: [email protected]

This research was supported by German Research Foundation (DFG) Grants HU 1510/4-1

and JA 1761/5-1. We thank Marina Astahova and Liliya Sergieva for their help in conducting

the experiments. We are also grateful to John Henderson, Todd Horowitz, and two anonymous

reviewers for their helpful comments on an earlier version of this paper.

VISUAL COGNITION, 2010, 18 (9), 1368�1391

# 2010 Psychology Press, an imprint of the Taylor & Francis Group, an Informa business

http://www.psypress.com/viscog DOI: 10.1080/13506285.2010.495878

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different camera angles. Hence, viewers have to keep track of the attended

players and the ball across abrupt viewpoint changes. In this study, we show

using a multiple object tracking (MOT) paradigm that gaze behaviour across

filmic cuts relies on mechanisms ensuring visual stability. When trackingthree objects across abrupt viewpoint changes, observers focus on a virtual

object (such as the invisible centre of mass of three objects) that includes as

vertices the tracked targets in the scene (Yantis, 1992). Most important, the

time spent looking at targets decreased after a viewpoint change, whereas

gaze time on the centroid remained more constant in total duration thr-

oughout the trial. Centroid looking that was proven as more important at

higher object speeds might enable humans to successfully track multiple

objects across abrupt viewpoint changes.Research on visual attention showed that observers can visually track

multiple objects that move independently (e.g., Alvarez & Franconeri, 2007;

Cavanagh & Alvarez, 2005; Pylyshyn & Storm, 1988). In standard multiple

object tracking displays, the frame or background around the moving ob-

jects remains stable throughout the entire trial. More recently, visual track-

ing was examined in nonstable scenes (Huff, Jahn, & Schwan, 2009; Huff,

Meyerhoff, Papenmeier, & Jahn, 2010; Liu et al., 2005; Seiffert, 2005). The

scene containing the objects remained no longer stable on the display butunderwent changes like rotations, zooms, or translations. It was shown, that

continuity of both object and scene motion seems to support visual tracking.

Abrupt changes such as translations of the whole scene or abrupt rotations

impair tracking performance considerably (Huff et al., 2009; Seiffert, 2005).

However, tracking performance was still above chance level after discontin-

uous translations and even if the reference frame was rotated abruptly by

308. Because in these conditions retinocentric coordinates suddenly change,

targets have to be recollected by means of scene-based coordinates. A group-ing strategy such as centroid looking codes a target’s location in relation to

other targets and may support tracking even if the scene as a whole moves

and retinocentric coordinates are lost.

How does the visual system manage to keep track of multiple objects?

First, human observers can only gaze at one object at a time. When tracking

more than one object there are at least two reasonable strategies: Target

jumping (Landry, Sheridan, & Yufik, 2001) or looking at a location within

the target group that minimizes the distance to each target. Recently, severalstudies examined gaze behaviour in MOT (Fehd & Seiffert, 2008; Zelinsky

& Neider, 2008; see also Doran, Hoffman, & Scholl, 2009). Those studies

manipulated the number of targets in either a standard MOT task (Fehd

& Seiffert, 2008) or in tracking sharks in a more realistic underwater scene

(Zelinsky & Neider, 2008). In both studies, MOT stimuli were presented in

a frame that remained stable throughout the trial and eye tracking results

were compared between conditions with different numbers of targets. In the

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one-target condition, gaze cumulated on the target, whereas in the three-

targets condition the so-called ‘‘centroid looking strategy’’ was observed:

Gaze was not only directed on targets but was also directed on the target

group’s centre of mass. Differences in the relative importance of the centroid

may be due to differences in object speed. When tracking three targets*and

under the assumption that each and every gaze is related with an object*about 66% of gaze positions were related with the centroid if objects moved

at 158/s (Fehd & Seiffert, 2008), whereas approximately 39% of gaze posi-

tions were related with the centroid if object speed was approximately 18/s(Zelinsky & Neider, 2008). However, assigning each gaze to an object might

result in an overestimation of gaze on objects. Nonetheless, observers seem

to look at the centroid in order to keep track of the targets by means of

a perceptual grouping strategy such as proposed by Yantis (1992). He found

that instructing participants to group several single targets into an object of

higher order (e.g., three targets into a triangle) enhanced tracking per-

formance (see also Alvarez & Oliva, 2008).

Centroid looking does not only occur in visual tracking but was also

observed in studies examining saccadic eye movements. If objects are pre-

sented in the periphery and participants are instructed to look at the targets

as a whole, saccades typically land on the centre of gravity of the shape

formed by the object group even if this centroid is located outside the shape

(McGowan, Kowler, Sharma, & Chubb, 1998; Vishwanath & Kowler, 2003).

This suggests that successful MOT in unstable displays*where observers

frequently have to realign their gaze*might benefit from centroid looking as

well.So far, centroid looking has been studied in stable scenes*what happens

if this stability is distorted? Unpredictable scene motion such as an abrupt

viewpoint change shifts target locations. If all target objects are integrated

into one geometric object that is tracked, this object moves in the same way

as the scene. The target group holds its specific geometric characteristics

(e.g., an isosceles triangle) within the three-dimensional scene space as its

location within the scene is specified in relation to other scene elements at

a given point of time. Successful visual tracking across abrupt viewpoint

changes requires the recollection of the target objects after an abrupt view-

point change and could be thought of as aligning the target group anchored

at the centroid to the new viewpoint. Because abrupt viewpoint changes lead

to larger translations of targets than of the centroid, observers might look at

the centroid more often than on the targets during this critical phase.Based on these deliberations we presume that abrupt viewpoint changes

may enhance the advantages of centroid looking in MOT. More specifically,

we hypothesize that abrupt viewpoint changes decrease gaze on the target

objects more than gaze on the centroid.

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EXPERIMENTAL OVERVIEW

In this study, we aim to examine gaze behaviour in the course of MOT trials

in order to compare gaze behaviour on target objects and on the centroid

before and after abrupt viewpoint changes. We hypothesize that increasing

the difficulty of MOT stimuli by introducing abrupt viewpoint changes and

by increasing object speed should result in extended centroid looking. The

presumed increase in the adoption of centroid looking in more difficult

MOT tasks was tested in two experiments. In both experiments, we mani-

pulated abrupt viewpoint changes and object speed. Because looking at the

centroid indicates grouping of the targets and tracking across a viewpoint

change is possible by realigning the target group, we expected centroid

looking to gain in importance for successful tracking when abrupt viewpoint

changes occur. More specifically, we hypothesize that gaze on the targets

would decrease more than gaze on the centroid after the abrupt viewpoint

change. Furthermore, in previous studies, the relative importance of the

centroid was the higher the faster the objects moved. Whereas Fehd and

Seiffert (2008) used a very high object speed (158/s), Zelinsky and Neider’s

(2008) sharks had an average velocity of 1.138/s. Increasing object speed

increases the difficulty of looking at single targets and thus the centroid

integrating the target group should increase in importance (Alvarez & Oliva,

2008). Consequently, the centroid looking strategy should gain in impor-

tance. In order to prevent anticipation of the viewpoint change we intro-

duced variable time points of the rotations in Experiment 2. Additionally, we

tested a wider range of object speeds. If centroid looking is reliable it should

hold with these manipulations too.

EXPERIMENT 1

In Experiment 1, observers tracked three targets moving among distractors

on a rectangular floor plane. We manipulated object speed in three levels (2,

4, and 68/s). In half of the trials, the scene was stable; in the other half an

abrupt viewpoint change of 208 occurred (see Figure 1). All conditions were

presented intermixed. Observers’ eye movements were recorded throughout

the MOT trials.

Method

Participants. Twenty students of the University of Tubingen (15 female,

five male; mean age�23.7 years) participated in this experiment that lasted

approximately 75 min. All participants reported normal or corrected to nor-

mal vision and received course credit or a monetary compensation for their

participation.

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Apparatus. Eye movements were recorded with a Tobii 1750 eye tracking

equipment running at 50 Hz providing a mean accuracy of 0.58. A chin- and

headrest made sure that participants kept a distance of 55 cm to the monitor.

Stimuli were created in real time with a Pentium IV 3 GHz computer using

Blender 2.45 (http://www.blender.org/) and custom software written in Python

(http://www.python.org/). They were presented via a 17-inch monitor in a 34.28(wide)�27.68 (high) viewable area at a resolution of 1280�1024 pixels.

Stimuli and procedure. Each participant was tested individually in a ses-

sion comprising 12 training and 120 experimental trials. Prior to testing,

a calibration procedure was carried out. Once calibrated, participants were

allowed to move their eyes freely on the screen. At the beginning of each

trial, eight small white spheres that were surrounded by a black cartoon-like

border were positioned randomly on a floor plane.1 Each sphere subtended

1.38 to 2.28 of visual angle. The floor grid was recorded with a camera angle

of 208 to the x-y plane and subtended 17.78 to 30.88 (wide)�8.48 (high) of

visual angle (see Figure 1). After 2 s, three objects flashed red four times

for 1.6 s at 200 ms intervals and then remained red for another 2 s. This

designated the target set that observers were to track through a period of

motion. The marked objects then turned back to white and all objects began

to move at a constant speed of 2, 4, or 68/s (when moving horizontally in the

centre of the floor plane) for a period of 5 s. Objects moved along the floor

in straight lines in a randomly chosen direction until they reached the edge

of the floor plane. Upon meeting the floor edge, an object’s trajectory was

changed so that it appeared to bounce off the edge and continued on a tra-

jectory consistent with the physics of a billiard ball moving at a constant

Figure 1. Example of the stimulus material. These two pictures depict the dynamic scene right before

and after the abrupt viewpoint change of 208. To view this figure in colour, please see the online issue

of the Journal.

1 Examples of the stimuli are available on our webpage (http://www.iwm-kmrc.de/

cybermedia/et/).

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speed. Object boundaries were allowed to intersect. In half of the trials, the

camera viewpoint changed abruptly within the motion period after 3 s of

motion (‘‘viewpoint change’’ conditions). The camera was repositioned 208along an imaginary horizontal circle around the vertical axis through the

centre of the floor plane. On half of the trials with viewpoint changes the

camera jumped to the right (counterclockwise on the imaginary circle) and

on the other half it jumped to the left. After viewpoint changes, the motion

period continued for 2 s. At the end of the 5 s period of continuous motion,

all of the objects stopped moving and the participants’ task was to indicate

the target objects by mouse click. Marked objects turned red. Participants

received feedback about the total number of correctly marked targets and

proceeded to the next trial by pressing the spacebar. Participants were ins-

tructed to respond accurately but to guess when uncertain. The experiment

started with 12 practice trials before formal testing began. Each participant

performed 120 experimental trials (2 levels of viewpoint change�3 levels of

object speed�20 repetitions).

Results and discussion

Due to calibration problems, five participants were excluded from data ana-

lysis. For the remaining 15 participants, proportion correct and eye tracking

data were analysed. We report partial eta2 (hp2) as effect-size measure.

Tracking accuracy. Proportion correct was defined as the number of cor-

rectly identified targets divided by three (total number of targets). Chance

performance was accordingly .375. Tracking performance as shown in Table 1

declined with increasing object speed, F(2, 28)�35.16, pB.001, hp2�.72,

and was lower with viewpoint changes, F(1, 14)�33.87, pB.001, hp2�.71.

The interaction of object speed and viewpoint change was not significant,

F(2, 28)�1.48, p�0.246, hp2�0.10. These results are consistent with pre-

vious findings (e.g., Huff et al., 2009; Scholl, Pylyshyn, & Feldman, 2001).

TABLE 1Tracking performance in Experiment 1 (with SD in parentheses)

Speed Viewpoint change Proportion correct

28/s 08 .97 (.02)

208 .89 (.05)

48/s 08 .92 (.04)

208 .82 (.08)

68/s 08 .84 (.07)

208 .78 (.09)

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Gaze behaviour. Eye tracking data in previous studies (Fehd & Seiffert,

2008; Zelinsky & Neider, 2008) were analysed with the so-called ‘‘shortest

distance rule’’, which assigns each gaze to its nearest object. This method is

based on the assumption that every gaze during a trial is directed towards anobject. This is fine for stable scenarios but becomes problematic if the scene

moves abruptly. In that case, not every gaze may be directed towards an

object. In fact, it seems very likely that in trials with abrupt scene motion,

some eye movements are not directed towards objects, at least in a short

interval after abrupt scene motion. Thus, we applied an alternative method

of coding and analysing eye movements. We defined every moving object

and the moving centroid of the target objects as separate areas of interest

(AOI). Only looking on the objects or the centroid was defined as a match.Eye movements not related with a defined AOI were coded as a miss.

As we were interested in how human observers manage keeping track of

multiple targets across abrupt viewpoint changes, we selected the trials, in

which all targets were identified correctly. Based on these criteria, 31.9% of

all trials were discarded. The 20 repetitions per condition ensured that at

least five trials per condition entered the final analysis for each participant.

Each moving object and the targets’ three-dimensional centroid were defined

as separate dynamic AOIs subtending 1.38 to 2.28 of visual angle dependenton their location on the floor plane. Overall, 43.5% of gaze was explained by

the a priori defined AOIs (28/s: 46.6%, 48/s: 41.9%, 68/s: 42.0%; see Figure 2).

Every 20 ms (50 Hz) we registered whether the participant’s gaze matched an

AOI. Those matches were summed up for each AOI (three targets, seven

distractors, and the targets’ centroid) in 500 ms intervals. The measure ‘‘pro-

portion matched’’ was calculated by dividing the sum of valid matches

per AOI by the total amount of possible matches. Finally, averages were

calculated for each AOI type, if a type consisted of more than one AOI. Forinstance, the proportions of gaze positions matching single distractors

were averaged to yield the mean proportion of gaze positions matching

a distractor.

Figure 2 shows the mean proportions of gaze positions matching the

AOI types separately for the 500 ms intervals in each condition. To test for

differences in gaze behaviour across the intervals statistically, we calculated

separate one-way ANOVAs including the within-subjects factor ‘‘interval’’

for each AOI-type (targets, distractors, and centroid) in each condition aswell as a planned contrast (t-test) between the 500 ms intervals on either side

of the abrupt viewpoint change in the viewpoint change conditions. The

results of these analyses are displayed in Table 2. In all conditions without

a viewpoint change, gaze behaviour did not change significantly across trial

intervals, FsB1.35, ps�.217, hp2sB.09. With viewpoint changes, gaze be-

haviour showed a drop and recovery of gaze on targets but not on the

targets’ centroid.

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Independent of object speed, viewpoint changes caused a significant dec-

line of gaze on target AOIs, F(9, 126)�3.00, p�.003, hp2�.18, F(9, 126)�

2.44, p�.013, hp2�.17, F(9, 126)�3.32, p�.001, hp

2�.19 for 2, 4, and 68/s

Figure 2. Time course analysis based on 500 ms intervals in Experiment 1. Results show stable gaze

allocation in the 08 viewpoint change condition. In the 208 viewpoint change conditions, significantly

less gaze on the targets was observed in the interval right after the abrupt viewpoint change. Most

importantly, gaze on the centroid dropped less than gaze on targets.

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object speed, respectively. This decline was followed by a significant increase

in the second interval after the viewpoint change up to the level before the

viewpoint change, pairwise t-tests pB.05, The time spent gazing on the cen-

troid differed less between the intervals before and after the viewpoint

change with 2 and 48/s object speed, F(9, 126)B1, p�.889, hp2�.06, and

F(9, 126)�1.29, p�.250, hp2�.08, respectively. At 68/s object speed, we

observed higher variability of gaze on the centroid resulting in a significant

main effect, F(9, 126)�3.19, p�.002, hp2�.19. Pairwise t-tests, however,

evinced that gaze on the centroid was not influenced by the abrupt viewpoint

change. Instead, significant differences were observed between intervals

4 and 5 as well as between intervals 9 and 10 (pairwise t-tests pB.05).Further analysis examined the total amount of gaze on centroid and tar-

gets in Experiment 1. First, we observed a significant interaction between

AOI type (targets and centroid) and object speed, F(2, 28)�10.41, pB.001,

hp2�.42. Planned post hoc analysis showed that centroid looking clearly

grew in importance with increasing object speed, F(2, 28)�9.00, pB.001,

hp2�.39, whereas higher object speed led to a decline of gaze on targets,

TABLE 2ANOVA results of the time course analyses of the data plotted in Figure 3; t-tests

reflect planned contrasts between 500 ms intervals before and after the abruptviewpoint change in Experiment 1

Viewpoint

change

Speed

(8/s) AOI F(9, 126) p hp2

Sign. diff. (pairwise t-tests,

pB.05) are starred (abrupt viewpoint

change between

intervals 6 and 7)

08 2 Target B1 .973 .02 1 � 2 � 3 � 4 � 5 � 6 � 7 � 8 � 9 � 10

Centroid B1 .684 .05 1 � 2 � 3 � 4 � 5 � 6 � 7 � 8 � 9 � 10

Distractor 1.35 .217 .09 1 � 2 � 3 � 4 � 5 � 6 � 7 � 8 � 9 � 10

4 Target B1 .841 .04 1 � 2 � 3 � 4 � 5 � 6 � 7 � 8 � 9 � 10

Centroid B1 .924 .03 1 � 2 � 3 � 4 � 5 � 6 � 7 � 8 � 9 � 10

Distractor B1 .748 .04 1 � 2 � 3 � 4 � 5 � 6 * 7 � 8 � 9 � 10

6 Target B1 .814 .04 1 � 2 � 3 � 4 � 5 � 6 � 7 � 8 � 9 � 10

Centroid B1 .924 .03 1 � 2 � 3 � 4 � 5 � 6 � 7 � 8 � 9 � 10

Distractor B1 .748 .04 1 � 2 � 3 � 4 � 5 � 6 � 7 � 8 � 9 � 10

208 2 Target 3.00 .003 .18 1 � 2 � 3 � 4 � 5 � 6 * 7 * 8 � 9 � 10

Centroid B1 .899 .06 1 � 2 � 3 � 4 � 5 � 6 � 7 � 8 � 9 � 10

Distractor 3.23 .001 .19 1 � 2 � 3 � 4 � 5 � 6 * 7 � 8 � 9 � 10

4 Target 2.44 .013 .17 1 * 2 * 3 � 4 � 5 � 6 * 7 * 8 � 9 � 10

Centroid 1.29 .250 .08 1 � 2 � 3 � 4 � 5 � 6 � 7 * 8 � 9 � 10

Distractor 1.36 .210 .09 1 � 2 � 3 � 4 � 5 � 6 � 7 � 8 � 9 � 10

6 Target 3.32 .001 .19 1 � 2 � 3 � 4 � 5 � 6 * 7 * 8 � 9 � 10

Centroid 3.19 .002 .19 1 � 2 � 3 � 4 * 5 � 6 � 7 � 8 � 9 * 10

Distractor B1 .627 .05 1 � 2 � 3 � 4 � 5 � 6 � 7 � 8 � 9 � 10

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F(2, 28)�7.40, p�.002, hp2�.35 (see Figure 3). Linear trend analyses

confirmed this finding, F(1, 14)�18.49, p�.001, hp2�.57, and F(1, 14)�

10.79, p�.005, hp2�.44, respectively.

Taken together, results from the analysis of gaze behaviour across trial

intervals showed that gaze behaviour is stable across successful track-

ing trials in conditions without abrupt viewpoint changes. Viewpoint chan-

ges caused a decline of gaze on targets but not on the centroid following

the viewpoint change. Centroid looking was observed at all object

speeds and became more important with increasing object speeds as

hypothesized.

A large proportion of gaze was directed towards targets and the centroid.

In contrast, looking towards distractors was rare. In the conditions with

Figure 3. Gaze on target and centroid AOIs in Experiment 1. With increasing object speed, gaze on

the centroid increased while gaze on targets decreased. Error bars indicate the standard error of the

mean.

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viewpoint change, gaze on the targets decreased significantly in the interval

right after the viewpoint change, whereas gaze on the centroid did not. After

these 500 ms, gaze behaviour was the same as before the viewpoint change.

While reorienting and realigning the targets, participants look at the cen-

troid of the target group.

Centroid looking as observed with stable scenes (Fehd & Seiffert, 2008;

Zelinsky & Neider, 2008) was replicated in the present experiment with scenes

undergoing abrupt viewpoint changes. Data from Experiment 1 suggest gaze

to be more stable on the centroid than on target objects. However, we

observed high variability of gaze on the centroid in the higher object speed

conditions. One reason for this increased variability could be that the

exclusion criterion (only trials with perfect tracking performance were inclu-

ded in the analysis) was not strict enough. Maybe participants sometimes

tracked only two targets and guessed the third correctly by chance. This

might have happened more frequently at higher object speeds and could

have increased gaze variability. In the second experiment we added a con-

fidence rating asking participants if they were able to track all objects. Only

trials in which participants tracked all objects correctly and in which

they stated that they were able to track all objects were included in the

analysis. Higher spatial and temporal resolutions as provided by the

SMI iView X Hi-Speed eye tracking system deployed in Experiment 2

should reduce gaze variability further. Furthermore, the improved temporal

resolution allowed us to look at saccade measures to further clarify our

results.

Another improvement in Experiment 2 concerns the predictability of the

viewpoint change. Centroid looking right after the viewpoint change could

be the result of an anticipation strategy. As the centroid is relatively stable (it

moves slower and its degree of movement is restricted) and the viewpoint

change occurred after 3 s in each trial, it might be possible that participants

directed their gaze strategically towards the centre of the targets right before

the viewpoint change. Such a strategy would not reflect spontaneous gaze

behaviour. Hence, we varied the viewpoint change time randomly to prevent

anticipation.

EXPERIMENT 2

Our objective in Experiment 2 was to replicate the findings of Experiment 1

for a wider range of object speeds. We manipulated object speed in two levels

(4 and 108/s). Additionally, we varied the time point of the abrupt viewpoint

change (2, 3, 4 s after the beginning of the scene) in order to prevent

anticipation. Gaze behaviour was recorded with a SMI iView X Hi-Speed

eye tracking system.

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Method

Participants. Eighteen students of the University of Tubingen (13 female,

five male; mean age�24.2 years) participated in this experiment and rep-

orted normal vision. They received compensation for their participation.

Apparatus. Stimuli were created the same way as in Experiment 1 and

were presented via a 19-inch monitor in a 31.68 (wide)�25.58 (high) viewable

area at a resolution of 1280�1024 pixels. Eye movements were recorded

with a SMI iView X Hi-Speed eye tracking system providing high spatial and

temporal resolutions (500 Hz). Mean calibration accuracy was 0.228 for the

x-coordinate and 0.298 for the y-coordinate. Gaze data were prepared with

DynAOI, a tool designed for matching gaze data to a priori defined AOIs in

3-D scenes (Papenmeier & Huff, 2010). A chin- and headrest made sure that

the participants kept a distance of 66 cm from the display.

Stimuli and procedure. Stimulus material was similar to Experiment 1

with four exceptions. First, object speed was either 4 or 108/s. Second, in

order to prevent anticipation of the viewpoint change, we added some

uncertainty with respect to the time point of the abrupt viewpoint change.

Viewpoint changes occurred 2, 3, or 4 s following the beginning of object

motion. Third, the training phase was two-tailed. In the first part consisting

of 24 trials, participants were given feedback about their tracking per-

formance. In the second part, consisting of four trials, participants had to

answer the following question as confidence rating: ‘‘Did you manage to

track all targets correctly?’’ Participants used the mouse to click on the

corresponding answer: ‘‘Yes’’ or ‘‘no’’. Fourth, in the experimental phase

participants were not provided with any feedback. Instead, they were asked

to answer the confidence rating after each trial. Taken together, each

participant performed 120 experimental trials in a 2 (4 vs. 108/s object

speed)�2 (with vs. without viewpoint change)�30 repetitions per condition

within-subjects design.

Results and discussion

Tracking performance. Results were similar to Experiment 1. Tracking

performance as shown in Table 3 declined with increasing object speed,

F(1, 17)�207.61, pB.001, hp2�.92, and was lower with viewpoint changes,

F(1, 17)�54.76, pB.001, hp2�.76. The interaction of object speed and

viewpoint change was not significant, F(1, 17)�1.87, p�.189, hp2�.10.

Gaze behaviour. Compared to Experiment 1, we tightened the selection

criterion for the gaze behaviour analysis. We selected the trials, in which all

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targets were identified correctly and participants stated that they were able to

keep track of all targets in the confidence rating. The 30 repetitions per

condition ensured that at least three trials per condition entered the final

analysis for each participant*except for the viewpoint change condition

with 108/s object speed. In this specific condition, we had to exclude four

participants from analysis because they had less than three trials with correct

tracking performance and perfect confidence. In sum, we discarded 58.1% of

all trials (25.4% in the no viewpoint change condition with 48/s object speed,

55.9% in the viewpoint change condition with 48/s object speed, 67.0% in

the no viewpoint change conditions with 108/s object speed, and 83.9% in

the viewpoint change condition with 108/s object speed). Overall, 40.8% of

gaze was explained by the a priori defined AOIs (48/s: 42.9%, 108/s: 35.8%;

see Figure 4).

In Experiment 1, viewpoint changes occurred after 3 s in each trial. In

Experiment 2, the time points of the viewpoint change varied between 2 and

4 s after the beginning of the trial. Hence, we cannot analyse gaze behaviour

across the entire tracking interval. Therefore, we analysed gaze behaviour

across the 500 ms intervals on either side of the viewpoint change plus the

second 500 ms interval after the viewpoint change (see Figure 4 and Table 4).

We calculated separate within subjects ANOVAs with the independent

variable ‘‘time interval’’ and the dependent measure proportion matched for

each AOI type in each condition. In all conditions without a viewpoint

change, gaze behaviour did not change significantly across trial intervals (all

hp2sB.16; see Table 4). For conditions with viewpoint changes, we were able

to replicate the finding in the condition with 48/s object speed. Here, gaze

behaviour showed a similar drop and recovery of gaze on targets as in

Experiment 1, F(2, 34)�9.60, pB.001, hp2�.36. In contrast, gaze on the

centroid was not affected by the viewpoint change, F(2, 34)B1, p�.440,

hp2�.05.

We observed different gaze behaviour in conditions with 108/s object

speed. Here, gaze on both centroid and target AOIs was not influenced

across the three time intervals (all hp2sB.02). As tracking three objects

moving in straight lines at 108/s is very error prone (we had to discard

TABLE 3Tracking performance in Experiment 2 (with SD in parentheses)

Speed Viewpoint change Proportion correct

48/s 08 .93 (.04)

208 .83 (.07)

108/s 08 .76 (.09)

208 .68 (.08)

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83.89% of the trials for this analysis) this analysis is based on very few trials

resulting in noisy data (see Figure 4 and Table 4).

As in Experiment 1, we examined the relationship between object speed

and gaze spent on centroid and mean target AOIs for the three intervals

around the viewpoint change. First, we observed a significant interaction

between AOI type (targets and centroid) and object speed, F(1, 13)�4.97,

p�.044, hp2�.28, replicating the findings from Experiment 1. Centroid

looking grew in importance with increasing object speed. Although there

was no difference between centroid and mean target AOIs in conditions with

48/s object speed, with 108/s we recorded significantly more gaze on the

centroid than on the mean target AOIs (pairwise Holm-corrected t-tests, pB

.05; see Figure 5). In addition, compared to mean target AOIs, more gaze

was recorded on the centroid AOI, F(1, 13)�12.17, p�.004, hp2�.48.

Finally, there was no main effect of object speed on the total amount of gaze

spent on centroid and mean target AOIs, FB1.

Figure 4. Gaze behaviour across 500 ms intervals in Experiment 2.

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Because the degrees of movement of the centroid are restricted*it is

located close to the centre of the floor plane most of the time*it is necessary

to exclude two possible alternative explanations of the findings. First, if

participants reorient by looking at the centre of the floor plane after the

abrupt viewpoint change, the observed centroid looking could be an artifact.

In order to exclude this possibility, we summed up the gaze positions with-

in a region of the size of a single object (subtending 1.75 degrees of visual

angle) on the centre of the floor plane and calculated the corresponding

ANOVA with the independent variable ‘‘interval’’. There was no influence

of the ‘‘interval’’ on gaze on the centre, F(2, 34)�2.35, p�.112, hp2�.12.

In particular, there was no increase of gaze after the abrupt viewpoint

change.

Second, results may be influenced by variability of eye movement right

after the abrupt viewpoint change. For example, if participants focus on the

centroid right before the abrupt viewpoint change and if participants do not

saccade at all but keep their eyes still after the abrupt viewpoint change,

one might expect that gaze stays within the centroid AOI for a considerable

amount of time. Accordingly, the observed result pattern would not indicate

centroid looking. In order to control for gaze variability across trials, we cal-

culated the mean number of saccades within the relevant three 500 ms

intervals (one interval before and two intervals after the viewpoint change).

Saccades were detected using an eye-velocity criterion of 308/s, Data as

reported in Table 5 were submitted to within-subject ANOVAs including the

independent variable ‘‘time interval’’ and the dependent variable ‘‘mean

TABLE 4ANOVA results of the gaze behaviour across trial intervals in Experiment 2; plannedcontrasts between time intervals before and after the abrupt viewpoint change were

performed with t-tests

Viewpoint

change Speed (8/s) AOI F P hp2

Planned contrast (t-test)

between intervals before and

after the viewpoint change

08 4 Target F(2, 34)B1 .494 .04

Centroid F(2, 34)B1 .675 .02

Distractor F(2, 34)�3.32 .048 .16

10 Target F(2, 34)�2.62 .087 .13

Centroid F(2, 34)�1.19 .315 .07

Distractor F(2, 34)�1.07 .354 .06

208 4 Target F(2, 34)�9.60 B.001 .36 t(17)�4.24, pB.001

Centroid F(2, 34)B1 .440 .05 t(17)�1.15, p�.264

Distractor F(2, 34)�1.58 .220 .09 t(17)�1.71, p�.106

10 Target F(2, 26)B1 .906 .01 t(13)�0.05, p�.963

Centroid F(2, 26)B1 .789 .02 t(13)�0.24, p�.812

Distractor F(2, 26)�3.41 .048 .21 t(13)�2.03, p�.063

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number of saccades’’ that were calculated separately for each condition. We

did not find any influence of the viewpoint change on the number of

saccades, all hp2sB.08. Hence, we can exclude the possibility of participants

just staring at the screen after the abrupt viewpoint change. Taken together,

centroid looking in the interval after the abrupt viewpoint change is real and

not a consequence of mere staring at the centre of the screen.

Transitions across abrupt viewpoint changes

Abrupt viewpoint changes suddenly displace the retinocentric representa-

tion of the 3-D scene. Do participants rematch their gaze position to the

displaced position of the previously fixated visible or invisible object across

Figure 5. Gaze on target and centroid AOIs in Experiment 2. With increasing object speed, gaze on

the centroid increased while gaze on targets decreased. Error bars indicate the standard error of the

mean.

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the viewpoint change or are there transitions between objects, for example

from a target to the centroid, or vice versa? If gaze positions were equally

likely rematched to the displaced position of a specific target or the centroid,

the drop of gaze on the targets might be caused by the larger target dis-

placement than centroid displacement possibly requiring more time to

re-match the gaze position to the displaced target locations than centroid

locations. For this analysis, we examined gaze behaviour in successful trials

of the 48/s condition with viewpoint change across all participants (perfect

tracking and perfect confidence rating). We defined transitions across

viewpoint changes as pairs of two object AOIs: The last object AOI that

gaze was matched with in the interval 500 ms before the viewpoint change

and the first object AOI that gaze was matched with in the interval 500 ms

following the viewpoint change. In order to identify valid transitions, we

removed gaze matches with the floor plane and misses as well as gaze

matches with object AOIs lasting less than 10 ms, thus removing spurious

matches caused by noise or bypassing saccades. Additionally, we removed

all transitions taking less than 10 ms because these did not result from

programmed saccades. As we were particularly interested in the difference

between gaze on target AOIs and the centroid AOI, we analysed transitions

starting and ending on target AOIs or the centroid AOI only. In total, there

were more transitions to the same object AOI (n�44) than to an object AOI

of the opposite category (target-centroid and centroid-target transitions, n�19), x2(1, N�63)�9.92, p�.002. Separating transitions as to whether they

started on a target AOI or centroid AOI, they did not differ in their

preference for ending on the very same object AOI or the object AOI of the

TABLE 5Mean number of saccades using a 308/s eye velocity criterion in Experiment 2 (withSD in parentheses); in conditions with 208 viewpoint change, the viewpoint change

occurred between intervals 1 and 2

Viewpoint change Speed (8/s) Interval Saccades

08 4 1 1.01 (0.56)

2 1.01 (0.55)

3 0.93 (0.47)

10 1 0.97 (0.52)

2 0.93 (0.72)

3 1.08 (0.91)

208 4 1 1.00 (0.66)

2 0.98 (0.47)

3 1.08 (0.59)

10 1 1.12 (0.74)

2 1.08 (0.84)

3 1.10 (0.70)

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opposite category, x2(1, N�63)�1.15, p�.283 (see Table 6). We thus

compared the time following the viewpoint change needed to re-match gaze

from a target AOI to the same target AOI (M�244 ms) and centroid AOI to

the same centroid AOI (M�217 ms) using a Wilcoxon rank sum test and

found no significant difference, W�227.5, p�.504. Hence despite larger

target displacements and the equal likelihood of making a transition to the

same object AOI rather than the object AOI of the opposite category for

targets and the centroid, the drop on target AOIs as described in the gaze

behaviour analysis cannot be explained by re-matching processes consuming

more time for targets than for the centroid.

Saccade analyses

So far, we showed a drop of gaze on target AOIs opposed to the centroid

AOI in the 500 ms following the viewpoint change. Furthermore, transitions

from a target AOI to the same target AOI take as long as transitions from

the centroid AOI to the centroid AOI. In order to gain further insights on

the difference of gaze to centroid and target AOIs following a viewpoint

change, we analysed the first saccades elicited by and therefore starting

within the 500 ms following the viewpoint change in the 48/s object speed

conditions irrespective of the previously fixated object AOIs across all

participants (perfect tracking and perfect confidence rating). We used a 308/seye-velocity threshold criterion for detection of the saccades. Consider-

ing the first saccade following the viewpoint change, there were 18 saccades

to the centroid AOI and 44 saccades to any target AOI. A Wilcoxon rank

sum test reveals that the time until the first saccade to the centroid AOI

(M�183 ms) is significantly shorter than the time until the first saccade to a

target AOI (M�266 ms), W�251, p�.024, thus showing that the centroid

of the target set can be computed very quickly in successful trials. This

difference cannot be explained in terms of saccade amplitude as the amp-

litude of saccades directed to the centroid AOI (M�2.688) did not differ

TABLE 6Total number of transitions across the abrupt viewpoint change for targets and the

centroid to either the same object AOI or an object AOI of the opposite category (targetto centroid or centroid to target transitions) in Experiment 2

AOI before viewpoint change

AOI after viewpoint change Target Centroid

Same object 31 13

Opposite category 10 9

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significantly from the amplitude of saccades directed to a target AOI (M�2.158) as revealed by a Wilcoxon rank sum test, W�495, p�.125.

Further, we analysed all saccades to target and centroid AOIs in the

500 ms intervals surrounding the viewpoint change. Although there wasan equal number of saccades to the centroid AOI (n�19) and to the mean

target AOI (n�16.67) in the 500 ms before the viewpoint change, x2(1, N�35.67)�0.15, p�.696, and in the second 500 ms interval following view-

point change (n�20 for centroid AOI, n�17 for mean target AOI), x2(1,

N�37)�0.24, p�.621, things look different in the interval right after

the viewpoint change. For the first 500 ms following the viewpoint change

there were more saccades to the centroid AOI (n�30) than the mean tar-

get AOI (n�17), x2(1, N�47)�3.60, p�.058. Summarizing, results fromthe saccade analyses suggest that the centroid can be computed very

quickly and that the centroid as a stable reference for the target set is

used when it comes to relocate the target objects after abrupt viewpoint

changes.

The goal of Experiment 2 was to replicate the findings of Experiment 1

showing that gaze on the centroid is more stable than gaze on targets. In

Experiment 2 we were able to replicate the central findings using an eye

tracking system with high temporal and spatial resolution. This enabledus to calculate additional analysis, like gaze transitions across the ab-

rupt viewpoint change and saccade goals after the viewpoint change.

Further, we tightened the selection criterion in Experiment 2 by analys-

ing trials with perfect tracking performance and perfect confidence rating

only. That is, participants stated that they guessed no target. Moreover,

we ruled out the alternative hypothesis according to which centroid looking

as described in Experiment 1 might have been the result of an anticipa-

tion strategy because the viewpoint change occurred always after 3 s. Al-though this is unlikely as trials with and without viewpoint change were

presented intermixed, we added some uncertainty with respect to the time

point of the viewpoint change in Experiment 2. Finally, we wanted to test

if the observed positive relation between object speed and gaze time spent

on the centroid also holds for a wider range of object speeds (4 and

108/s).

Despite all these changes, we were able to replicate the central findings of

Experiment 1. Viewpoint changes caused a decline of gaze on targets but notthe centroid. Centroid looking was observed at all object speeds and became

more important with increasing object speeds as hypothesized.

Although we were able to replicate the central findings of Experiment 1 in

the 48/s condition (drop and recovery of gaze on targets in the first 500 ms

interval after the abrupt viewpoint change), there was no influence of the

viewpoint change on gaze behaviour at all in the 108/s condition. Pre-

sumably, the tracking task was too difficult.

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GENERAL DISCUSSION

The reported experiments studied effects of scene motion and object speed

on eye movements. Observers’ gaze behaviour was recorded while they trac-

ked multiple moving objects across abrupt viewpoint changes. Abrupt

changes of the display holding the objects shift retinocentric coordina-

tes, which usually results in lower tracking performance (Huff et al., 2009;

Seiffert, 2005). How do human observers recollect targets after abrupt scene

motion? A reasonable strategy is perceptual grouping (Yantis, 1992). Look-

ing at the centroid that is defined as the targets’ centre of mass could indicate

such a strategy. Consistent with this presumption, gaze on the centroid

declined less after abrupt viewpoint changes than gaze on targets, which was

reduced for about 500 ms after the abrupt viewpoint change. Furthermore,

we demonstrated for the first time within the same experiment that centroid

looking gains in importance at higher object speeds.

Gaze behaviour during MOT was examined in two recent studies (Fehd

& Seiffert, 2008; Zelinsky & Neider, 2008). In both studies, a considerable

amount of gaze was directed towards the centre of mass of the target group

when three targets were tracked. This so called ‘‘centroid looking strategy’’

was stronger in the Fehd and Seiffert (2008) study, which employed higher

object speed than in the Zelinsky and Neider (2008) study. These results

suggest a positive correlation between object speed and amount of cen-

troid looking: When tracking gets more strenuous more gaze related with

the centroid was observed. We confirmed this assumption in both of our

experiments.

We hypothesized that after an abrupt viewpoint change the targets are

recollected by aligning the target group to the new viewpoint indicated by

gaze related with the centroid. We confirmed this hypothesis in Experiment 1

and Experiment 2 by showing that the centroid was looked at even right

after a viewpoint change when observers successfully recollected shifted

targets.

There are several benefits that centroid looking might provide in tracking

and recollecting targets. First, pursuing the centroid that represents the

target group by a single spatial coordinate prevents that any target moves far

from focal vision where peripheral vision quickly blurs. This may be an

advantage over a target jumping strategy, in which a single focused target

benefits from highest visual resolution. However, the distance from this

target located in the fovea to the nonfocused targets is larger than the mean

distance between the targets and the corresponding centroid. As a result,

with target jumping the nonfocused targets are located further in the

periphery increasing the probability of being lost. Second, the centroid’s

velocity and degrees of movement are restricted compared to single targets.

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And finally, the average displacement caused by an abrupt viewpoint change

is less for the centroid than for targets.

In the current study, with increasing task difficulty*either due to the

occurrence of an abrupt viewpoint change (no matter if its time point couldbe anticipated as in Experiment 1 or not as in Experiment 2) or due to

increasing object speed (Experiment 1 and 2)*the relative amount of

centroid looking increased. Presumably, our participants made use of some

or all of the benefits of centroid looking.

The present analysis of eye tracking data differs substantially from pre-

vious studies (Fehd & Seiffert, 2008; Zelinsky & Neider, 2008). Whereas in

our study gaze data were analysed with the dynamic AOI approach (every

gaze on an a priori defined AOI was coded as a match and all other gazeswere coded as a miss), previous studies employed the ‘‘shortest distance

rule’’ that assigns every gaze to its nearest object. The dynamic AOI ap-

proach as implemented in this study explained about 35�47% of gaze. This is

a reasonable proportion because the total size of the AOIs (targets, dis-

tractors, and centroid) is far less than 35% of the display size (see Figure 1).

One way of increasing the amount of gaze explained by the dynamic AOI

approach could be to increase the size of the dynamic AOIs. In our study the

AOI size equalled the object size. However, increasing AOIs becomesproblematic as this would result in a lot of overlaps of the different AOIs.

In this context, it should be noted that the proportion of gaze identified as

centroid looking differs substantially between the previous studies (Fehd &

Seiffert, 2008; Zelinsky & Neider, 2008) and our study. Whereas in previ-

ous studies the proportion was 66% and 39% (Fehd & Seiffert, 2008, and

Zelinsky & Neider, 2008, respectively), in our study about 10% of gaze was

identified as centroid looking. However, considering the lower overall

proportion of gaze explained by the dynamic AOI approach, this value isclose to the proportion of centroid looking found in previous studies. Taken

together, although the eye tracking methodology applied in this study

differed in various aspects from previous experiments, it seems to be quali-

tatively equivalent to the ‘‘shortest distance rule’’.

Both methods*‘‘dynamic AOI’’ and ‘‘shortest distance rule’’*need the

a priori definition of objects and do not consider any other strategies. Maybe

gaze on targets and centroid do not account for all gaze in multiple object

tracking. For example, it is conceivable that some gaze is not only relatedwith real and virtual objects like the centroid. Instead, gaze could be

distributed more in the picture plane between the targets. In this case, the

dynamic AOI approach as applied in this study would be a good estimator of

the real gaze behaviour as it does not falsely assign gaze to the nearest

object.

How does the visual system calculate the positions of the centroid after

the viewpoint change without knowing the exact locations of the targets?

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From the additional analyses of Experiment 2 we know that centroid look-

ing is not the result of just staring at the centre of the floor plane or reduced

saccade frequencies after the viewpoint change. Further, we know that the

gaze position across the viewpoint change is most likely to be rematched tothe displaced position of the previously looked at object and that this

rematching process takes as long for targets as the centroid. At first sight,

these results suggest that there was no preference for centroid looking when

it comes to relocating targets following a viewpoint change. Having a closer

look at the data by taking all saccades in the intervals surrounding the

viewpoint change into account, we showed that there is a preference for

saccades to the centroid AOI over the mean target AOI in the first 500 ms

following the viewpoint change only. That is, there is a preference in lookingat the centroid for relocating the targets. Even more interesting in respect to

the process underlying centroid calculation is the analysis of the first saccade

following the viewpoint change. We found that the first saccade following

the viewpoint change is more quickly directed towards the centroid than the

targets and that the saccade to the centroid starts in mean only 183 ms

following the viewpoint change. Considering research on the relationship of

attention and saccades showing that attention shifts to the target of a sac-

cade prior to the occurrence of the saccade (e.g., Hoffman & Subramaniam,1995; Posner, 1980; Shepherd, Findlay, & Hockey, 1986), our results suggest

that the centroid is calculated almost instantly following the viewpoint

change. Thus, the process underlying centroid calculation must be working

very efficiently and might be supported by the recognition of the target set as

a perceptual group (Yantis, 1992). As the centroid is a stable representation

of the targets (it moves slower and its degrees of movements are restricted), it

is the most favourite goal of gaze when visual tracking gets harder and

especially after abrupt viewpoint changes.From an evolutionary point of view, the visual system cannot be adapted

to abrupt and unpredictable viewpoint changes yet, since the time period

from the introduction of the first edited movies (around 1900; Kuleshov,

1920/1974) is too short. A recent study has shown that there is a difference

between first time film viewers and experienced viewers in understanding

viewpoint changes within a scene (Schwan & Ildirar, 2010). Whereas

experienced viewers do understand such viewpoint changes first time viewers

do not. Therefore, it would be worth comparing gaze data of experiencedand inexperienced viewers during an MOT task including abrupt viewpoint

changes.

The abrupt scene motion employed in the reported experiments was

a rotational viewpoint change. Hence, target translations were larger than

centroid translations. Further studies with equidistant translations of all

objects (including targets, distractors, and centroid) are needed to gain fur-

ther insight in the gaze behaviour while tracking across abrupt changes in

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general. This could be done by simple horizontal translations of the floor

plane. An important question will be if the relative amount of centroid

looking is comparable to the one shown in this study. A first hypothesis

about gaze behaviour while tracking across abrupt translations can bededuced from research on saccadic localization. If objects are presented in

the periphery and subjects were instructed to look at the targets as a whole,

saccades typically land at the centre of gravity of the shape even if this is

located outside the shape (McGowan et al., 1998; Vishwanath & Kowler,

2003). If visual tracking relies on grouping the single targets into an object

of higher order, it seems plausible that gaze behaviour with equidistant

translations of targets and centroid is comparable to gaze behaviour with

rotational viewpoint changes; observers should be able to efficiently use thecentroid in recollecting target objects.

REFERENCES

Alvarez, G. A., & Franconeri, S. L. (2007). How many objects can you track? Evidence for

a resource-limited attentive tracking mechanism. Journal of Vision, 7(13), 1�10. doi:10.1167/

7.13.14.

Alvarez, G. A., & Oliva, A. (2008). The representation of simple ensemble visual features outside

the focus of attention. Psychological Science, 19(4), 392�398. doi:10.1111/j.1467-9280.

2008.02098.x.

Cavanagh, P., & Alvarez, G. A. (2005). Tracking multiple targets with multifocal attention.

Trends in Cognitive Sciences, 9(7), 349�354. doi:10.1016/j.tics.2005.05.009.

Doran, M., Hoffman, J. E., & Scholl, B. (2009). The role of eye fixations in concentration and

amplification effects during multiple object tracking. Visual Cognition, 17(4), 574�597.

doi:10.1080/13506280802117010.

Fehd, H. M., & Seiffert, A. E. (2008). Eye movements during multiple object tracking: Where do

participants look? Cognition, 108(1), 201�209. doi:10.1016/j.cognition.2007.11.008.

Hoffman, J. E., & Subramaniam, B. (1995). The role of visual attention in saccadic eye move-

ments. Perception and Psychophysics, 57(6), 787�795.

Huff, M., Jahn, G., & Schwan, S. (2009). Tracking multiple objects across abrupt viewpoint

changes. Visual Cognition, 17(3), 297�306. doi:10.1080/13506280802061838.

Huff, M., Meyerhoff, H. S., Papenmeier, F., & Jahn, G. (2010). Spatial updating of dynamic

scenes: Tracking multiple invisible objects across viewpoint changes. Attention, Perception,

and Psychophysics, 72(3), 628�636. doi:10.3758/APP.72.3.628.

Kuleshov, L. (1974). Kuleshov on film (R. Levaco, Trans.), Berkeley, CA: University of California

Press. (Original work published 1920)

Landry, S. J., Sheridan, T. B., & Yufik, Y. M. (2001). A methodology for studying cognitive

groupings in a target-tracking task. IEEE Transactions on Intelligent Transportation Systems,

2(2), 92�100. doi:10.1109/6979.928720.

Liu, G., Austen, E. L., Booth, K. S., Fisher, B. D., Argue, R., Rempel, M. I., et al. (2005).

Multiple-object tracking is based on scene, not retinal, coordinates. Journal of Experimental

Psychology: Human Perception and Performance, 31(2), 235�247. doi:10.1037/0096-1523.

31.2.235.

McGowan, J., Kowler, E., Sharma, A., & Chubb, C. (1998). Saccadic localization of random dot

targets. Vision Research, 38, 895�909. doi:10.1016/S0042-6989(97)00232-0.

1390 HUFF ET AL.

Downloaded By: [Huff, Markus] At: 05:14 28 September 2010

Papenmeier, F., & Huff, M. (2010). DynAOI*A tool for matching eye movement data with

dynamic areas of interest in animations and movies. Behavior Research Methods, 42,

179�187. doi:10.3758/BRM.42.1.179.

Posner, M. I. (1980). Orienting of attention. Quarterly Journal of Experimental Psychology, 32,

3�25. doi:10.1080/00335558008248231.

Pylyshyn, Z. W., & Storm, R. W. (1988). Tracking multiple independent targets: Evidence for

a parallel tracking mechanism. Spatial Vision, 3(3), 179�197. doi:10.1163/156856888X00122.

Scholl, B. J., Pylyshyn, Z. W., & Feldman, J. (2001). What is a visual object? Evidence from

target merging in multi-element tracking. Cognition, 80, 159�177. doi:10.1016/S0010-0277

(00)00157-8.

Schwan, S., & Ildirar, S. (2010). Watching film for the first time: How adult viewers interpret

perceptual discontinuities in film. Psychological Science, 21(7), 970�976. doi:10.1177/09

56797610372632.

Seiffert, A. E. (2005). Attentional tracking across display translations. Journal of Vision, 5(8),

643a. doi:10.1167/5.8.643.

Shepherd, M., Findlay, J. M., & Hockey, R. J. (1986). The relationship between eye movements

and spatial attention. Quarterly Journal of Experimental Psychology, 38A, 475�491.

Vishwanath, D., & Kowler, E. (2003). Localization of shapes: Eye movements and perception

compared. Vision Research, 43(15), 1637�1653. doi:10.1016/S0042-6989(03)00168-8.

Yantis, S. (1992). Multielement visual tracking: Attention and perceptual organization.

Cognitive Psychology, 24(3), 295�340. doi:10.1016/0010-0285(92)90010-Y.

Zelinsky, G. J., & Neider, M. B. (2008). An eye movement analysis of multiple object tracking in

a realistic environment. Visual Cognition, 16(5), 553�566. doi:10.1080/13506280802000752.

Manuscript received May 2009

Manuscript accepted May 2010

First published online September 2010

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