Robust Object Tracking Algorithm using Harris Detector based Bayesian Filters

  • Neetu Gupta, MunishVashishath, Rajiv Kapoor

Abstract

Computer vision systems represent an essential tool for a broad range of video surveillance applications. Two of the most noteworthy challenges for these systems are Object tracking and anomalous activity detection. Numerous algorithms were developed for the purpose of tracking, e.g In this research work the objective of object tracking for anomaly detection has been achieved by making use of filters. The filters that have been used for tracking and anomaly detection are the Bayes Filters. They work on the concept of prediction. The idea is to get samples of the posterior distribution from the hidden states .This paper presents the Particle filter combined with the Harris feature descriptor for tracking moving objects in a video

Published
2020-02-21
How to Cite
Rajiv Kapoor, N. G. M. (2020). Robust Object Tracking Algorithm using Harris Detector based Bayesian Filters. International Journal of Advanced Science and Technology, 29(3), 3578 - 3590. Retrieved from https://sersc.org/journals/index.php/IJAST/article/view/4842
Section
Articles