Object Tracking with Correlation Filters using Selective Single Background Patch

TL;DR

This paper introduces a novel object tracking method that utilizes a single background patch and a modified correlation filter with image restoration, achieving improved accuracy and robustness in benchmark tests.

Contribution

It proposes a new approach to select a single background patch and modifies correlation filters with image restoration techniques for better tracking.

Findings

Enhanced tracking accuracy on benchmark sequences

Effective background patch selection improves robustness

Modified correlation filter outperforms traditional methods

Abstract

Correlation filter plays a major role in improved tracking performance compared to existing trackers. The tracker uses the adaptive correlation response to predict the location of the target. Many varieties of correlation trackers were proposed recently with high accuracy and frame rates. The paper proposes a method to select a single background patch to have a better tracking performance. The paper also contributes a variant of correlation filter by modifying the filter with image restoration filters. The approach is validated using Object Tracking Benchmark sequences.