An Improved TLD Visual Tracking and Detection Algorithm Based on Depth Image Information
Jialiang Jialiang Mao, Xiaorong Shen · 2016
Tracking-Learning-Detection(TLD) algorithm has the advantages of high speed, high accuracy of tracking rate and self-detection mechanism.However the sensitivity to illumination variation and background clutter leads to drift even miss for TLD algorithm under the complex environment.An improved TLD visual tracking algorithm based on depth information is proposed, which is improved from three aspects.The first is that a foreground extraction algorithm based on denoised depth data is adopted to extract the region of interest.Second, a sophisticated detection of blob approach is used to narrow down the searching area.And the third is that the non-maximal suppression strategies are applied to optimize the result.The experimental results show that the time complexity of proposed is decreased and the robustness is upgrade under challenging circumstances.