final ppt

VIDEO SEGMENTATION

Prepared By:-Himanshu Kumar

GEC/085159

WHAT IS VIDEO?•Video technology was first developed for cathode ray tube television systems.

•Video is the technology of electronically capturing, recording, processing, storing, transmitting, and reconstructing a sequence of still images representing scenes in motion.

•Video can be recorded and transmitted in various physical media.

Videos are Image Sequences over Time

• 25 Images/s• An image is a function f( x , y , t)=ft( x , y)• At each time step t we

have an image f( x , y)• Frame rate = the

number of images per second.

y

x

t

VIDEO FRAMES•In film, video production, animation, and related fields, a frame is one of the many still images which compose the complete moving picture.

•When the moving picture is displayed, each frame is flashed on a screen for a short time.

•The frame rate, the rate at which sequential frames are presented, varies according to the video standard in use.

I-FRAMES

•I-frames are called as intracoded frames.

•I-frame is a single frame of digital content.

•The more I-frames that are contained, the better quality the video will be.

B-FRAMES

•B-frames rely on the frames preceding and following them.

•B-frames contain only the data that have changed from the preceding frame.

•They provide the highest level of compression.

P-FRAMES•P (predicted) frames are coded using the nearest previous reference (I or P) pictures.

•A P‑frame holds only the changes in the image from the previous frame.

•. P‑frames are also known as delta‑frames.

APPLICATION OF VIDEO•VIDEO COMPRESSION –Video compression refers to reducing the quantity of data used to represent digital video images.

•VIDEO ENHANCEMENT –A method of improving the definition of a video picture by a computer program.

•VIDEO SEGMENTATION –Video segmentation aims to partition the video to elementary image sequences termed scenes and shots.

VIDEO

SEGMENTATION

SEGMENTATION IN VIDEO•Finding the object(s) -

Preprocessing, segmentation

Knowledge base

Problemdomain

Imageacquisition

Preprocessing

SegmentationRepresentationand description

Recognitionand Interpretation

Result

SEGMENTATION

SEGMENTATION•Separation of Foreground (object) and Background (everything else = noise).

•Result could be a - Binary image - Containing foreground only

•Useful for further processing, such as using silhouettes, etc.

SEGMENTATIONUSING

MOTION

SEGMENTATION USING MOTION

•Assume that only the object is moving => motion can be used to find the object.

•Motion detection - Image differencing - Background subtraction

IMAGE

DIFFERENCING

IMAGE DIFFERENCING•The motion in an image can be found by subtracting the current image from the previous image•Algorithm:-1.Save image in last frame2.Capture current camera image3.Subtract image (= difference = motion)4.Threshold5.Delete noise

SUBTRACT

IMAGE

SUBTRACT IMAGE

•Compute pixel-wise

•Subtract previous image from input image: F(x , y)= I(x ,y) – B(x , y)

•Usually the absolute distance is applied |F(x , y)|

THRESHOLD

THRESHOLDDecide, when a pixel is supposed to be considered as a background pixel, or when it is to be considered as a foreground pixel:

Pixel (x ,y) is foreground pixel, if |F(x , y)| > TH

Pixel(x , y)is background pixel, if |F(x , y)| <TH

DELETING

NOISE

DELETING NOISE

•Single pixels are likely to appear: Pixel-noise!!

•Apply Median filter:Depending on filter size, bigger spots can be erased

•Alternative: Morphology

BACKGROUND

SUBTRACTION

BACKGROUNDSUBTRACTION

• Foreground is moving, background is stable.

• Algorithm:-1. Capture image containing background2. Capture camera image3. Subtract image (difference = motion)4. Threshold5. Delete noise

APPLICATIONS OF VIDEO SEGMENTATION

•Video segmentation based on multiple features for interactive multimedia applications.

•Application of video segmentation to video surveillance.

•Movie scene segmentation using background information.

•Video segmentation utilized in visual data mining applications. •Video summarization.

•Indexing and retrieval.

REFERENCES[1] I. Pitas, Digital image processing algorithms (Englewood Cliffs,NJ: Prentice Hall, 1993).  [2] A. Hampapur, R. Jain, and T.Weymouth, “Feature based digital video indexing,” in IFIP 2.6 ThirdWorking,Conference on Visual Database Systems, Lausanne, Switzerland, 1995. [3] L. Wu, J. Benois-Pineau, and D. Barba, “Spatio-temporal segmentation of image sequences for objectoriented low bit-rate image coding,” Image Communication, Vol. 8, No. 6, pp. 513–544, 1996. [4]B. Furht, S.W. Smoliar, and H.J. Zhang, Video and Image Processing in Multimedia Systems, 2nd edition, Kluwer Academic Publishers: Norwell, USA, 1996.

[5] Boreczky, J.S. and Rowe, L.A. Comparison of video shotboundary detection techniques. Storage and Retrieval forStill Images and Video Databases IV, Proc. of SPIE 2670,pp. 170-179, 1996. 

[6] N. Haering, R. Qian, and I. Sezan, “A semantic event-detection approach and its application to detectinghunts in wildlife video,” IEEE Transactions on Circuits and Systems for Video Technology, Vol. 10, No. 6,pp. 857–868, 2000. [7] K. El-Maleh, M. Klein, G. Petrucci, and P. Kabal, “Speech/music discrimination for multimedia applications,”in IEEE International Conference on Acoustics, Speech, and Signal Processing, Istanbul, Turkey, 2000,pp. 2445–2448.

[8] S. Y. Chien, S. Y. Ma, and L. G. Chen “Efficient Moving Object Segmentation Algorithm UsingBackground Registration Technique”, IEEE Trans. on circuits and system for video technology, Vol. 12, No.7, pp. 577–586, July 2002.  [9] Gonzalez, R.C. and Woods, R.E.,Digital Image Processing - Second Edition.Upper Saddle River: Prentice-Hall 2002 

 [10] P. L. Rosin and E. Ioannidis, “Evaluation of global image thresholding for change detection,” PatternRecognition Letters, vol. 24, pp. 2345–2356, 2003. [11] Shao-Yi Chien, Yu-Wen Huang, Bing-Yu Hsieh, Shyh-Yih Ma, and Liang-Gee Chen,“Fast VideoSegmentation Algorithm with Shadow Cancellation, Global Motion Compensation, and Adaptive ThresholdTechniques,” IEEE Trans. on Circuits and System for Video Technol., Vol. 6, pp. 732-748, No. 5, October.2004.

[12] www.wikipedia.org/ [13] www.sciencedirect.com/ [14] ieeexplore.ieee.org/Xplore/guesthome.jsp [15] www.google.co.in/

THANKS!