Visual Tracking System for Target Representation and Localization

Authors

  • Sandhya Gopal Alhat  Department of Computer Engineering, P.E.S. Modern College of Engineering, Savitribai Phule, Pune University, Maharashtra, India
  • Dr. B. D. Phulpagar  Department of Computer Engineering, P.E.S. Modern College of Engineering, Savitribai Phule, Pune University, Maharashtra, India

Keywords:

Color Histograms, Local Steering Kernels, Visual Object Tracking, Kalman Filter.

Abstract

Visual object tracking is the process in which objects in video sequences are tracked. The transformations the target object in motion undergoes like rotation, scale, change in view angle, illumination variations, partial and full occlusion in sequence of video frames have paved way for various representation methods and tracking algorithms. Here in this paper we propose a system for visual object tracking, which offers a representation of the targeted object depending on its appearance that is based on local steering kernel descriptor (LSK) as well as color histogram data. The input for the system is taken as the previous video frame as well as stored instance of object which is targeted. By searching the frame region we try to locate the target object in present frame which best resembles the target object input. The object model stores the instances of the target object and it gets updated as the view of the target object changes over time. The surrounding background as well as color histogram similarity in object which is decoded is utilized for the purpose of background subtraction. Given that the transformations in target object between two consecutive frames are rather small, the implemented system has been proven to be successful in tracking more than one target objects in a video and it also handles the case of full occlusion. We are keeping track of the LSK matrices of pervious frame and comparing it with the LSK matrices of the current frame to detect the target object and used Kalman filter to correct the predicted target object location.

References

  1. Zoidi, A. Tefas and I. Pitas, "Visual Object Tracking Based on Local Steering Kernels and Color Histograms," in IEEE Transactions on Circuits and Systems for Video Technology, vol. 23, no. 5, pp. 870-882, May 2013.
  2. Zhang, X. Gao, D. Tao and X. Li, "Image super-resolution via non-local steering kernel regression regularization," 2013 IEEE International Conference on Image Processing, Melbourne, VIC, 2013, pp. 943-946.
  3. He, H. Jing, Q. Han and X. Niu, "A Saliency Detection Approach to Combine LSK and Color for Color Image," Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP), 2011 Seventh International Conference on, Dalian, 2011, pp. 129-132.
  4. Luo, S. Ci, D. Wu, N. Stergiou and K. Siu, "A Remote Markerless Human Gait Tracking for E-Healthcare based on Content-aware Wireless Multimedia Communications", IEEE Wireless Commun., vol. 17, no. 1, pp. 44-50, Feb. 2010.
  5. Cavallaro, O. Steiger and T. Ebrahimi, "Tracking video objects in cluttered background", IEEE Trans. Circuits Syst. Video Technol., vol. 15, pp. 575-584, Apr. 2005.
  6. Yilmaz, X. Li and M. Shah, "Contour-based object tracking with occlusion handling in video acquired using mobile cameras", IEEE Trans. Pattern Anal. Mach. Intell., vol. 26, no. 11, pp. 1531-1536, Nov. 2004.
  7. Jeyakar, R. V. Babu and K. Ramakrishnan, "Robust object tracking with background-weighted local kernels", Comput. Vision Image Understanding, vol. 112, no. 3, pp. 296-309, 2008
  8. Zhou, R. Chellappa and B. Moghaddam, "Visual tracking and recognition using appearance: Adaptive models in particle filters", IEEE Trans. Image Process., vol. 13, no. 11, pp. 1434-1456, Nov. 2004.
  9. A Survey on Moving Object Tracking in Video - Barga Deori, Dalton Meiti Thounaojam, International Journal of Information Theory(IJIT), Vol3, July 2014
  10. Wang, G. Bebis, and R. Miller, “Robust Video-Based     Surveillance By Integrating Target Detection With         Tracking,” in Proc. Conf. CVPRW OTCBVS, June 2006.
  11. Adam, E. Rivlin, and I. Shimshoni, “Robust fragments-based tracking using the integral histogram,” in Proc. IEEE Conf. CVPR, Sep. 2006, pp. 798–805.
  12. Sathya Bharathi ,"Visual Object tracking mechanism"IOSR-JCE, Vol 16 Issue 3 May-June2014.
  13. Zoidi, A. Tefas , I. Pitas,"Visual Object Tracking Based on the Object’s Salient features with Application in Automatic Nutrition Assistance", IEEE International Conference, 31 August 2012.
  14. Nijad Al-Najdawi, Sara Tedmori, Eran Edirsinghe, and Helmut,"An Automated Real-Time People Tracking System Based on KLT Features Detection", IAJIT, vol .9, January 2012.
  15. Ramsey Faragher,"Understanding the Basis of the Kalman Filter via a Simple and Intuitive Derivation,"IEEE Signal Processing Magazine Sept. 2012.
  16. Anand Singh Jalal, Vrijendra Singh,"State of –the- Art in Visual Object Tracking", Informatica 36 (2012) 227-248.
  17. Papanikolopoulos, P. Khosla, and T. Kanade,"Visual tracking of a moving target by a camera mounted on a robot: A combination of control and vision,"IEEE Trans. Robot. Autom., vol. 9, Feb.1993.
  18. R. Bradski."Computer vision face tracking for use in a perceptual user interface,". in Proc. IEEE Workshop Appl. Comput. Vision, 1998.
  19. Yang, R. Duraiswami, and L. Davis,"Efficient Mean- Shift Tracking via a new similarity measure,"in Proc. IEEE Comput. Soc. Conf. Comput. Vision Pattern Recogn., vol. 1, Jun. 2005, pp. 176–183.
  20. Roller, K. Daniilidis, and H. H. Nagel,"Model-based object tracking in monocular image sequences of road traffic scenes,"Int. J. Comput.Vision, vol. 10, pp. 257– 281, Mar. 1993.
  21. Yilmaz, X. Li, and M. Shah,"Contour-based object tracking With occlusion handling in video acquired using mobile cameras,"IEEE Trans. Pattern Anal. Mach. Intell., vol. 26, no. 11, pp. 1531–1536, Nov.2004.
  22. Fan, M. Riihimaki, and I. Kunttu,"A feature-based object tracking approach for realtime image processing on mobile devices,"in Proc.17th IEEE ICIP, Sep. 2010, pp. 3921–3924.
  23. -Q. Xu and P. Puig,"A hybrid blob- and appearance- based framework for multi-object tracking through complex occlusions,"in Proc. 2nd Joint IEEE Int. Workshop Visual Surveillance Perform. Evaluation Tracking Surveillance, Oct. 2005, pp. 73–80.

International Journal of Scientific Research in Science, Engineering and Technology

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Published

2016-12-30

Issue

Volume 2, Issue 6, November-December-2016

Section

Research Articles

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How to Cite

[1]
Sandhya Gopal Alhat, Dr. B. D. Phulpagar, " Visual Tracking System for Target Representation and Localization, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 2, Issue 6, pp.584-592, November-December-2016.