Adaptive Color Attributes for Real-Time Visual Tracking

TLDR

Visual tracking is challenging, and while most state‑of‑the‑art trackers rely on luminance or simple color, sophisticated color features—when combined with luminance—have proven effective for recognition and detection, yet a color descriptor for tracking must be computationally efficient, photometrically invariant, and highly discriminative. The study investigates the role of color in a tracking‑by‑detection framework and proposes an adaptive low‑dimensional variant of color attributes. The authors evaluate the adaptive color attributes on 41 challenging benchmark color sequences using both quantitative metrics and attribute‑based analysis. The adaptive color attributes outperform the baseline intensity tracker by 24 % in median distance precision, surpass state‑of‑the‑art methods, and run at over 100 fps.

Abstract

Visual tracking is a challenging problem in computer vision. Most state-of-the-art visual trackers either rely on luminance information or use simple color representations for image description. Contrary to visual tracking, for object recognition and detection, sophisticated color features when combined with luminance have shown to provide excellent performance. Due to the complexity of the tracking problem, the desired color feature should be computationally efficient, and possess a certain amount of photometric invariance while maintaining high discriminative power. This paper investigates the contribution of color in a tracking-by-detection framework. Our results suggest that color attributes provides superior performance for visual tracking. We further propose an adaptive low-dimensional variant of color attributes. Both quantitative and attribute-based evaluations are performed on 41 challenging benchmark color sequences. The proposed approach improves the baseline intensity-based tracker by 24 % in median distance precision. Furthermore, we show that our approach outperforms state-of-the-art tracking methods while running at more than 100 frames per second.