Research and implementation of dynamic gesture recognition system based on ZYNQ

Abstract

At present, gesture has become an important channel of human-computer interaction, and gesture recognition has been widely used in various fields. In this paper, the dynamic gesture recognition technology is studied from algorithm and system implementation for portable devices which require high real-time performance. The algorithm mainly uses the region of interest extraction based on face recognition, skin color detection based on HCrCg color space and gesture motion track marking based on scanline seed filling algorithm. The system is implemented by Xilinx ZYNQ, and a SOPC system architecture based on ARM Cortex-A9 hard core and ARM Cortex-M3 soft core and FPGA is proposed. The scanline seed filling algorithm with long running time is designed as a hardware accelerator to improve the running speed. Through the test of the prototype, the recognition accuracy can reach 95.75% in a simple background and 90.83% in a complex background. The average running time of the system is only 0.68 seconds, which is more than 30% faster than using pure software method. The system has good performance in recognition accuracy and running speed.