A parallel optimization method for kernel correlation filter based on multi-core DSP

Target tracking is an important branch in the field of computer vision. In recent years, parallel computing efficiency becomes the key to improving real-time performance in multi-core DSP platforms. This paper proposes the concept of execution parallelism based on Open MP, optimizes Kernel Correlation Filter (KCF) with execution parallelism parameters, and compares it with inter-processor Communication (IPC). This paper aims at the KCF algorithm on the TMS320C6678 platform for the multi-core parallel development of the above two methods. With multiple data-sets, the results are all higher than 60 frames/s. With physical verification by connecting the video board, parallel scheme based on Open MP can achieve a tracking effect of 75 FPS, which has certain engineering practical significance.