PE-TLD: Parallel Extended Tracking-Learning-Detection for Multi-target Tracking

摘要

Multi-target tracking in video has been a research focus, with the combination of many fields, such as computer vision, artificial intelligence, pattern matching. In this paper, we present an efficient multi-target recognition and tracking algorithm based on TLD (Tracking-Learning-Detection), named PE-TLD. A new foreground extraction filter using ViBe is introduced to improve the speed and accuracy of detection. A new target recognition component is added, and core detector is improved. Based on that, we further implemented a parallel version, taking advantage of the state-of-the-art parallel computing techniques such as OpenMP and OpenCL, which runs efficiently on a system with both multi-core CPU and GPU. Experiments showed that PE-TLD is up to 5 times faster than the serial version. PE-TLD is an automatic multi-target recognition and tracking system, which is efficient enough to be deployed for real-time usage.