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Survey on Algorithms for Object Tracking in Video

by G. Lakshmeeswari, K. Karthik
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 141 - Number 13
Year of Publication: 2016
Authors: G. Lakshmeeswari, K. Karthik
10.5120/ijca2016909686

G. Lakshmeeswari, K. Karthik . Survey on Algorithms for Object Tracking in Video. International Journal of Computer Applications. 141, 13 ( May 2016), 17-22. DOI=10.5120/ijca2016909686

@article{ 10.5120/ijca2016909686,
author = { G. Lakshmeeswari, K. Karthik },
title = { Survey on Algorithms for Object Tracking in Video },
journal = { International Journal of Computer Applications },
issue_date = { May 2016 },
volume = { 141 },
number = { 13 },
month = { May },
year = { 2016 },
issn = { 0975-8887 },
pages = { 17-22 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume141/number13/24844-2016909686/ },
doi = { 10.5120/ijca2016909686 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:43:26.825973+05:30
%A G. Lakshmeeswari
%A K. Karthik
%T Survey on Algorithms for Object Tracking in Video
%J International Journal of Computer Applications
%@ 0975-8887
%V 141
%N 13
%P 17-22
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Object tracking is a very essential task in many applications of computer vision such as surveillance, vehicle navigation, autonomous robot navigation, etc. It contains detection of interesting moving objects and tracking of such objects from frame to frame. Its main task is to find and follow a moving object or multiple objects in image sequences. Normally there are three stages of video analysis: object detection, object tracking and object reorganization. This paper presents a brief survey of various video object tracking techniques like point tracking, kernel tracking and Silhouette tracking algorithms.

References
  1. A. B lake, B. Basc le, M. Isard, J. MacCorm ick, “Statistical models of visual shape and motion”, Phil. Trans. R. Soc. Lond. A (1998) 356, 1283–1302
  2. R. E. KALMAN “A New Approach to Linear Filtering and Prediction Problems”, Transactions of the ASME–Journal of Basic Engineering, 82 (Series D): 35-45. Copyright © 1960 by ASME
  3. Veenman CJ, Reinders MJT, Backer E (2001) “Resolving motion correspondence for densely moving points”. IEEE Trans on Pattern Analysis and Machine Intelligence 23(1):54–72
  4. Sethi IK, Jain R “Finding trajectories of feature points in a monocular image sequence”. IEEE Trans on Pattern Analysis and Machine Intelligence 9(1):56–73
  5. Salari V, Sethi I “Feature point correspondence in the presence of occlusion”. IEEE Trans on Pattern Analysis and Machine Intelligence 12(1):87–91
  6. K. Rangarajan, M. Shah. “Establishing motion correspondence”, CVGIP: Image Understanding, 54:56–73, 1991
  7. Michael J. Black, Allan D. Jepson “Eigen tracking: Robust matching and tracking of articulated objects using a view-based representation”. International Journal of Computer Vision 26(1), 63–84
  8. Prasad Kalane “Target Tracking Using Kalman Filter” International Journal of Science & Technology, ISSN (online): 2250,Vol. 2 Issue 2, April 2012
  9. Alper Yilmaz Omar, Mubarak Shah “Object tracking: A Survey”, ACM Computing Surveys, Vol. 38, No. 4, Article 13, Publication date: December 2006.
  10. P Fieguth, D Terzopoulos. “Color - based tracking of heads and other mobile objects at video frame rates”, Computer Vision and Pattern Recognition, 1997. Proceedings., IEEE
  11. 11. Jianbo Shi, Carlo Tomasi. “Good Features to Track”, IEEE Conference on Computer Vision and Pattern Recognition, pages 593–600, 1994.
  12. Dorin Comaniciu “Mean Shift: A Robust Approach Toward Feature Space Analysis” IEEE Transactions On Pattern Analysis And Machine Intelligence, Vol. 24, No.
  13. Bruce D. Lucas, Takeo Kanade. “An Iterative Image Registration Technique with an Application to Stereo Vision”, International Joint Conference on Artificial Intelligence, pages 674–679, 1981
  14. Carlo Tomasi, Takeo Kanade. “Detection and Tracking of Point Features”, Carnegie Mellon University Technical Report CMU-CS-91-132, April 1991.
  15. 
Index Terms

Computer Science
Information Sciences

Keywords

Object tracking point tracking kernel tracking silhouette tracking.

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