Sparse vs. Non-sparse: Which One Is Better for Practical Visual Tracking?

TL;DR

This paper compares sparse and non-sparse representation methods for visual tracking, demonstrating that non-sparse trackers can achieve similar accuracy with faster speed, making them more practical for real-world applications.

Contribution

The paper introduces a robust non-sparse visual tracker and provides extensive experimental comparison with sparse trackers, highlighting its competitive performance and efficiency.

Findings

Non-sparse tracker achieves comparable accuracy to sparse trackers.

Non-sparse tracker runs faster than sparse methods.

Results support using non-sparse methods in practical applications.

Abstract

Recently, sparse representation based visual tracking methods have attracted increasing attention in the computer vision community. Although achieve superior performance to traditional tracking methods, however, a basic problem has not been answered yet --- that whether the sparsity constrain is really needed for visual tracking? To answer this question, in this paper, we first propose a robust non-sparse representation based tracker and then conduct extensive experiments to compare it against several state-of-the-art sparse representation based trackers. Our experiment results and analysis indicate that the proposed non-sparse tracker achieved competitive tracking accuracy with sparse trackers while having faster running speed, which support our non-sparse tracker to be used in practical applications.