Subject Review: Image Processing Techniques for Object Tracking in Video Surveillance
DOI:
https://doi.org/10.31695/IJERAT.2022.8.8.3Keywords:
Digital Image Processing, Video Analytics, Video Surveillance Systems, Object Detection, Object TrackingAbstract
The article is devoted to real-time algorithms for detecting events described by four scenarios: movement in a forbidden direction, being in a sterile zone, leaving (stealing) an object, throwing an object. The main idea of the algorithms is the analysis of the trajectories of moving objects, for which two different approaches are proposed in the article.
References
Ainsworth T. Buyer Beware // Security Oz. 2002 Vol. 19. P. 18–26.
Single M. Motion Detection Based on Frame Difference Method International // Journal of Information & Computation Technology. 2014. Vol. 4. No. 15. P. 1559–1565.
Zivkovic Z. Improved adaptive Gaussian mixture model for background subtraction // IEEE Int. Conf. pattern recognition. 2004 Vol. 2. P. 28–31
Bouwmans T., El Baf F., Vachon B. Background Modeling using Mixture of Gaussians for Foreground Detection – A Survey // Recent Patents on Computer Science. 2008 Vol. 1. P. 219–237.
Dalal N., Triggs B. Histograms of Oriented Gradients for Human Detection // IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2005. P. 886–893.
Felzenszwalb P., Girshick R., McAllester D., Ramanan D. Object Detection with Discriminatively Trained Part Based Models // IEEE Transactions on Pattern Analysis and Machine Intelligence. 2010 Vol. 32. No. 9. P. 1627–1645.
Girshick R., Donahue J., Darrell T., Malik J. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation // IEEE Conference on Computer Vision and Pattern Recognition. 2014. P. 580–587.
Je C., Park H. M. Optimized Hierarchical Block Matching for Fast and Accurate Image Registration // Signal Processing: Image Communication. 2013. Vol. 28. No. 7. P. 779–791.
Aslani S., Mahdavi-Nasab H. Optical Flow Based Moving Object Detection and Tracking for Traffic Surveillance // International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering. 2013. Vol. 7. No. 9. P. 1252–1256.
Zaveri M. A., Merchant S. N., Desai U. B. Small and Fast Moving Object Detection and Tracking in Sports Video Sequences // IEEE International Conference on Multimedia and Expo. 2004 Vol. 3. P. 1539-1542.
Comaniciu D., Ramesh V., Meer P. Kernel-based object tracking // IEEE Transactions on pattern analysis and machine intelligence. 2003 Vol. 25. No. 5. P. 564–577.
Chitaliya N. G., Trivedi A. I. Novel block matching algorithm using predictive motion vector for video object tracking based on color histogram // 3rd International Conference on Electronics Computer Technology. 2011 Vol. 5. P. 81–85.
Hingane P., Shirsat S. Object Tracking Using Joint Color-Texture Histogram // International Journal of Science and Research. 2013. P. 2603–2606
Tissainayagama P., Suterb D. Object tracking in image sequences using point features // Pattern Recognition. 2005 Vol. 38. No. 1. P. 105–113.
Fischler M. A., Bolles R. C. Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography // Communications of the ACM 24. 1981. P. 381–395.
Downloads
Published
Issue
Section
License
Copyright (c) 2022 Ahmed Othman Khalaf, Shaimaa Khudhair Salah
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
