FPGA-based Volleyball Player Tracker

Abstract

The significant challenge facing sport science is how to grasp the flow of the game and analyze the situation of amatch. The use of information technology will facilitate to achieve the goal. The technical issues from the practical application perspective can be classified into three main points: computation speed, system size and complex data analysis considering the accuracy. In this paper, for accelerating image recognition and object tracking, we propose a one-dimensional data pipeline architecture on a field-programmable gate array (FPGA). It satisfies both of high-speed streaming computation and small-sized circuits by considering spatiotemporal data dependence. Volleyball games have been chosen as a target application. The proposed system will identify the position of six volleyball players within real time. The design on an FPGA includes pre-processing, color filtering, digitalization, noise reduction, template matching, and so on. The design was implemented and evaluated on Atlys Spartan-6 FPGA Trainer Board with one XILINX Spartan-6 LX45 FPGA. The computational performance achieves 100 frames per second at SVGA 800 by 600 pixel resolution. And our design has good scalability; the performance can easily be enhanced when the larger FPGA is used. The proposed system is also compact, which is composed of one Atlys board and one Atlys VmodCAM stereo-camera board. The average-accuracy rates of pregame situation and during a match are 87.1% and 65.7%, respectively. Since the input is streaming data, we can improve the accuracy by considering the previous and the next frames. They could be improved to 90.4% and 72.2%, respectively, when we adopt template matching with a moving average filter.