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

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

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

Applications of object tracking Object tracking in video scenes Automated video surveillance Robot vision Traffic monitoring Animation 11/22/2018 Object tracking in video scenes

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. 11/22/2018 Object tracking in video scenes

Steps in object tracking Object tracking in video scenes Preprocessing Segmentation Foreground/background extraction Feature extraction Tracking 11/22/2018 Object tracking in video scenes

Object tracking in video scenes Preprocessing Filtering Noise removal Uncompressing the compressed data 11/22/2018 Object tracking in video scenes

Object tracking in video scenes Segmentation Boundary detection Connected component labeling Thresholding 11/22/2018 Object tracking in video scenes

Foreground extraction Object tracking in video scenes Difference images Absolute Accumulative Difference Image Positive Accumulative Difference Image Negative Accumulative Difference Image Kalman filtering 11/22/2018 Object tracking in video scenes

Background extraction Object tracking in video scenes Image subtraction Background learning 11/22/2018 Object tracking in video scenes

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 11/22/2018 Object tracking in video scenes

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. 11/22/2018 Object tracking in video scenes

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) . 11/22/2018 Object tracking in video scenes

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 11/22/2018 Object tracking in video scenes

Object tracking in video scenes Compressed domain object tracking Based on color Based on motion vectors 11/22/2018 Object tracking in video scenes

System performance and architectural considerations Real time or offline processing Compressed domain data Cost v/s performance Video characteristics (frame rate, frame size) 11/22/2018 Object tracking in video scenes

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