Abstract
Systems for object detection and tracking are becoming increasingly important in practical applications today. Many research and development groups are interested in improving the performance of such systems, and numerous methods have been developed and proposed. Additionally, computer vision is constantly developing and implemented on reconfigurable and embedded systems. The purpose of this study is to present past and recent research works in the field of visual tracking systems that used FPGA and FPGA-SoC platforms. The study includes a brief description of several popular algorithms related to the main characteristics and in which field is preferred. Resource utilization was also considered in this study to present the most and the least resources used to implement different algorithms. The study found that flip-flops (FF) and lookup tables (LUT) are usually used, while BRAM, DSP, and multipliers had the lowest percentage utilization. Due to the recent development in the production of advanced processing systems, there is an increase focusing on employing FPGA-SoC platforms in visual surveillance systems. The reason behind that is their ability to implement complex processing using both hardware and software co-design to gain high performance in less design time compared with using only FPGA-based platforms.
