Human Tracking Under Severe Occlusions

Harihara Santosh Dadi*, Gopala Krishna Mohan Pillutla**, Madhavi latha Makkena***
* Associate Professor, Aditya Institute of Technology and Management, Hyderabad, India.
** Professor, Institute of Aeronautical College of Engineering, Hyderabad, India.
*** Professor, Department of Electronics and Communication Engineering, JNT University, Telangana, India.
Periodicity:July - September'2017
DOI : https://doi.org/10.26634/jse.12.1.13922

Abstract

Human tracking using surveillance cameras is a demanding topic of research now-a-days. Tracking and recognizing the human is much more challenging. There are many existing methods for tracking humans based on shapes and motion. In this paper, a novel algorithm for tracking human under occlusions is introduced. Gaussian Mixture Model (GMM) is used for tracking the human, which performs well under different occlusions. The new algorithm produces excellent results in case the human is occluded by another human and is obstructed by some other human, and also when there are partial occlusions. Experimental results show that the new algorithm outperforms in tracking the humans in these three cases.

Keywords

GMM, Occlusion, Human Tracking.

How to Cite this Article?

Dadi, H, S., Pillutla, G, K, H., and Makkena, M, L. (2017). Human Tracking Under Severe Occlusions. i-manager’s Journal on Software Engineering, 12(1), 29-37. https://doi.org/10.26634/jse.12.1.13922

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