A robust template tracking algorithm with weighted active drift correction

Baojie Fan

doi:10.1016/j.patrec.2011.03.010

Return

A robust template tracking algorithm with weighted active drift correction

2011-07-01

PRE

DOI：10.1016/j.patrec.2011.03.010

Original

Original request for help

Save

Abstract

En 中文

In this paper, we propose a novel algorithm for object template tracking and its drift correction. It can prevent the tracking drift effectively, and save the time of an additional correction tracking. In our algorithm, the total energy function consists of two terms: the tracking term and the drift correction term. We minimize the total energy function synchronously for template tracking and weighted active drift correction. The minimization of the active drift correction term is achieved by the inverse compositional algorithm with a weighted L2 norm, which is incorporated into traditional affine image alignment (AIA) algorithm. Its weights can be adaptively updated for each template. For diminishing the accumulative error in tracking, we design a new template update strategy that chooses a new template with the lowest matching error. Finally, we will present various experimental results that validate our algorithm. These results also show that our algorithm achieves better performance than the inverse compositional algorithm for drift correction. (C) 2011 Elsevier B.V. All rights reserved.

Keywords:

Template tracking

Inverse compositional algorithm

Active drift correction

Template update

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.