基于DSP的嵌入式目标跟踪系统

近年，由Henriques等人提出的核化相关滤波算法（KCF算法）在算法规模、复杂度、性能等方面表现优越.本文以KCF算法为核心，提出并设计了一种基于DSP的目标跟踪系统.硬件方面，本文设计实现了一套完整独立的硬件平台；软件方面，本文提出一系列针对DSP的算法优化方法，使优化后的KCF算法能够满足重要的工程指标要求.结果表明，系统在工程环境中表现良好，跟踪角速度可达20度/秒，平均帧率25 fps，跟踪准确率较高，为计算机视觉领域内的各类算法的嵌入式应用提供参考.

Embedded Target Tracking System Based on DSP

In recent years, the Kernel Correlation Filtering algorithm (KCF algorithm) proposed by Henriques et al. shows superior performance in terms of algorithm scale, computational complexity, and algorithm performance. Based on KCF algorithm, a target tracking system based on DSP is proposed and designed in this study. In terms of hardware, this study designs and implements a complete and independent hardware platform. In terms of software, this study proposes a series of algorithm optimization methods for DSP to optimize KCF algorithm, in order to meet the requirements of important engineering indicators. The results show that the system performs well in the actual engineering environment, the highest tracking angular velocity can be 20 degrees/s, and the frame rate can be 25 fps on average, and it has high accuracy. The system provides reference for embedded applications of various algorithms in the field of computer vision.