Robust and Accurate Human Tracking Algorithm for Handling Occlusion and Out of Plane Rotation
Anshul Pareek1, Nidhi Arora2

1Anshul Pareek*, ECE Deptt, Maharaja Surajmal Institute Of Technology, Delhi India.
1Dr. Nidhi Arora, CSE Department, G.D. Goenka University, Gurugram, India.

Manuscript received on September 16, 2019. | Revised Manuscript received on 24 September, 2019. | Manuscript published on October 10, 2019. | PP: 3768-3773 | Volume-8 Issue-12, October 2019. | Retrieval Number: L26821081219/2019©BEIESP | DOI: 10.35940/ijitee.L2682.1081219
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (

Abstract: Robust and accurate human tracking using computer vision is acquiring more and more attention, seeking to meet the demands of the increasing number of applications. This paper presents a novel approach to handle occlusion and out of plane rotation. Both these issues are crucial and continue to be a challenge in all state of art algorithms of computer vision-based human tracking. In this paper a SURF oriented scheme based human tracker is proposed, which searches for the target human in expanded rectangular region surrounding the previous target location. There is an online update of object model by selecting fresh templates every time. Here, superimposition of keypoints obtained from previous templates is done on fresh template using Affine transformation. Whether it’s a pose change or not, is affirmed by affine transformation, by calculating aspect ratio of target enclosed region. An Autotuned classifier discriminates the case of occlusion and pose change and confirms tracking failure. The success rate and computational time proves the accomplishment of the proposed algorithm
Keywords: Human Tracking, SURF, Grab-Cut Algorithm, UKF(Unscented Kalman Filter) and Autotuned Classifier.
Scope of the Article: Classification