Simultaneous Segmentation and 3D Pose Estimation of Humans or Detection + Segmentation = Tracking? Philip H.S. Torr Pawan Kumar, Pushmeet Kohli, Matt Bray Oxford Brookes University Andrew Zisserman Oxford Arasanathan Thayananthan, Bjorn Stenger, Roberto Cipolla Cambridge
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Simultaneous Segmentation and 3D Pose Estimation of Humans or Detection + Segmentation = Tracking?
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Simultaneous Segmentation and 3D Pose Estimation of Humans
orDetection + Segmentation = Tracking?
Philip H.S. TorrPawan Kumar, Pushmeet Kohli, Matt Bray
Gavrila) Idea: When matching similar objects, speed-up by
forming template hierarchy found by clustering Match prototypes first, sub-tree only if cost below
threshold
Trees
These search trees are the same as used for efficient nearest neighbour.
Add dynamic model and • Detection = Tracking = Recognition
Evaluation at Multiple Resolutions
One traversal of tree per time step
Evaluation at Multiple Resolutions
Tree: 9000 templates of hand pointing, rigid
Templates at Level 1
Templates at Level 2
Templates at Level 3
Comparison with Particle Filters
This method is grid based,• No need to render the model on line• Like efficient search• Can always use this as a proposal process for
a particle filter if need be.
Interpolation, MVRVM, ECCV 2006
Code available.
Energy being Optimized, link to graph cuts
Combination of• Edge term (quickly evaluated using chamfer)• Interior term (quickly evaluated using integral
images)
Note that possible templates are a bit like cuts that we put down, one could think of this whole process as a constrained search for the best graph cut.
Likelihood : Edges
Edge Detection Projected Contours
Robust EdgeMatching
Input Image 3D Model
Chamfer MatchingInput image Canny edges
Distance transform Projected Contours
Likelihood : Colour
Skin Colour ModelProjected Silhouette
Input Image 3D Model
Template Matching
Template Matching =
Template Matching = constrained search for a cut/segmentation?
Detection = Segmentation?
Objective
Image Segmentation Pose Estimate??
Aim to get a clean segmentation of a human…
MRF for Interactive Image Segmentation, Boykov and Jolly [ICCV 2001]