Authors:
Aysegul Dundar
;
Jonghoon Jin
and
Eugenio Culurciello
Affiliation:
Purdue University, United States
Keyword(s):
Tracking, SMR, Similarity Matching Ratio, Template Matching.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Motion, Tracking and Stereo Vision
;
Tracking and Visual Navigation
Abstract:
This paper presents a novel approach to visual tracking: Similarity Matching Ratio (SMR). The traditional approach of tracking is minimizing some measures of the difference between the template and a patch from the frame. This approach is vulnerable to outliers and drastic appearance changes and an extensive study is focusing on making the approach more tolerant to them. However, this often results in longer, corrective
algorithms which do not solve the original problem. This paper proposes a novel approach to the definition of the tracking problems, SMR, which turns the differences into probability measures. Only pixel differences below a threshold count towards deciding the match, the rest are ignored. This approach makes the SMR tracker robust to outliers and points that dramatically change appearance. The SMR tracker is tested on challenging video sequences and achieves state-of-the-art performance.