Best-Buddies Tracking

TL;DR

Best-Buddies Tracking (BBT) introduces a modified similarity measure based on Best-Buddies Similarity, enabling effective model-free online tracking that adapts to scale changes and variable template sizes within a particle filter framework.

Contribution

The paper proposes a modification to BBS to handle unequal point set sizes, improving its applicability to scale variations in online tracking.

Findings

Effective handling of scale changes in tracking.

Supports variable number of templates.

Achieves good results on standard benchmarks.

Abstract

Best-Buddies Tracking (BBT) applies the Best-Buddies Similarity measure (BBS) to the problem of model-free online tracking. BBS was introduced as a similarity measure between two point sets and was shown to be very effective for template matching. Originally, BBS was designed to work with point sets of equal size, and we propose a modification that lets it handle point sets of different size. The modified BBS is better suited to handle scale changes in the template size, as well as support a variable number of template images. We embed the modified BBS in a particle filter framework and obtain good results on a number of standard benchmarks.