Year: 2015
Type: conference-paper
Abstract: When appearance variation of object, partial occlusion or illumination change in object images occurs, most existing tracking approaches fail to track the target effectively.To deal with the problem, this paper proposes a robust visual tracking method based on sparse representation.To make the observation model more robust and reduce the requirement of storage space, the incremental learning algorithm is used to update the target templates.Experimental results demonstrate that in case of object deformation, partial occlusion and illumination change, the proposed visual tracking algorithm can still maintain better tracking accuracy and robustness
Author: Qiufen Yang
Institution: Hunan Radio and Television University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W1816097432