Robust Visual Tracking Based on Convex Hull with EMD-L1

Abstract

Factors such as drastic illumination variations, partial occlusion, rotation make robust visual tracking a difficult problem. Some tracking algorithms represent a target appearances based on obtained tracking results from previous frames with a linear combination of target templates. This kind of target representation is not robust to drastic appearance variations. In this paper, we propose a simple and effective tracking algorithm with a novel appearance model. A target candidate is represented by convex combinations of target templates. Measuring the similarity between a target candidate and the target templates is a key problem for a robust likelihood evaluation. The distance between a target candidate and the templates is measured using the earth mover’s distance with L1 ground distance. Comprehensive experiments demonstrate the robustness and effectiveness of the proposed tracking algorithm against state-of-the-art tracking algorithms.