Adaptive Color Attributes for Real-Time Visual Tracking

Visual tracking is a challenging problem in computer vi-sion. 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 ob-ject recognition and detection, sophisticated color features when combined with luminance have shown to provide ex-cellent performance. Due to the complexity of the tracking problem, the desired color feature should be computation-ally 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 bench-mark color sequences. The proposed approach improves the baseline intensity-based tracker by 24 % in median distance precision. Furthermore, we show that our approach out-performs state-of-the-art tracking methods while running at more than 100 frames per second. 1