1. Object tracking in video scenes Object tracking in video scenes
A seminar on
Object tracking in video scenes By
Alok K. Watve
M. Tech. IT 1st Year
IIT, Kharagpur
11/22/2018
Object tracking in video scenes

2. Object tracking in video scenes
Topics covered
Introduction
Applications
Related work
Steps in object tracking
Some existing algorithms for tracking
Conclusion
11/22/2018
Object tracking in video scenes

3. What is object tracking? Object tracking in video scenes
Object tracking can be defined as the process of segmenting an object of interest from a video scene and keeping track of its motion, orientation, occlusion etc. in order to extract useful information.
Three approaches:
Feature-based methods
Differential methods
Correlation
11/22/2018
Object tracking in video scenes

4. Applications of object tracking Object tracking in video scenes
Automated video surveillance
Robot vision
Traffic monitoring
Animation
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Object tracking in video scenes

5. Object tracking in video scenes
Related work
A. Gyaourova, C. Kamath, S. and C. Cheung - Block matching technique - LLNL Technical report, October 2003.
Y. Rosenberg and M. Werman - Object tracking using moving camera - Applications of Computer Vision, 1998.
Çiˇgdem Eroˇglu Erdem and Bülent San - Feedback-based method - IEEE Transactions on circuits and systems for video technology, vol. 13, no. 4, April 2003
Y. Wang, J. Doherty and R. Van Dyck – Feature based tracking - Proc. Conference on Information Sciences and Systems, Princeton, NJ, March 2000.
A. Turolla, L. Marchesotti and C.S. Regazzoni - Multiple camera model.
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Object tracking in video scenes

6. Steps in object tracking Object tracking in video scenes
Preprocessing
Segmentation
Foreground/background extraction
Feature extraction
Tracking
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Object tracking in video scenes

7. Object tracking in video scenes
Preprocessing
Filtering
Noise removal
Uncompressing the compressed data
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Object tracking in video scenes

8. Object tracking in video scenes
Segmentation
Boundary detection
Connected component labeling
Thresholding
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Object tracking in video scenes

9. Foreground extraction Object tracking in video scenes
Difference images
Absolute Accumulative Difference Image
Positive Accumulative Difference Image
Negative Accumulative Difference Image
Kalman filtering
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Object tracking in video scenes

10. Background extraction Object tracking in video scenes
Image subtraction
Background learning
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Object tracking in video scenes

11. Object tracking in video scenes
Camera modeling
Single fixed camera
Example: Road traffic tracking system
Multiple fixed cameras
Example: Simple surveillance system
Single moving camera
Example: Animation and video compression systems
Multiple moving cameras
Example: Robot navigation system
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Object tracking in video scenes

12. Object tracking in video scenes
Feature based object tracking
Centroid = ( cx, cy ) where,
cx = (pi,j * i )/ ( p i,j )
cy = (pi,j * j )/ ( p i,j )
dispersion = (  ( (I – cx)2 + ( j – cy )2)*pi,j ) / ( pi,j)
Grey scale distribution of the image is expressed in terms of grey scale range grm, mean of the higher 10% values grh and mean of lower 10% values grl.
Texture of the object tx is defined by the mean of higher 10% values in the wavelet edge image.
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Object tracking in video scenes

13. Object tracking in video scenes
Block matching method for tracking
Each block from the current frame is matched into a block in the destination frame by shifting the current block over a predefined neighborhood of pixels in the destination frame. The measure used is Mean Absolute Difference (MAD) .
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Object tracking in video scenes

14. Object tracking in video scenes
Tracking based on domain knowledge
Reduces complexity of the system
Traffic monitoring system – motion can be approximated by simple affine transformations
Where,
s = scaling factor,
u0 =displacement between two consecutive frames,
xm = the centre of the moving image region
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Object tracking in video scenes

15. Object tracking in video scenes
Compressed domain object tracking
Based on color
Based on motion vectors
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Object tracking in video scenes

16. System performance and architectural considerations
Real time or offline processing
Compressed domain data
Cost v/s performance
Video characteristics (frame rate, frame size)
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Object tracking in video scenes

17. Object tracking in video scenes
Conclusion
Wide area of application
Dependence on problem domain
Computation intensive, hence needs support from underlying hardware
11/22/2018
Object tracking in video scenes