A Hardware Architecture for Real-Time Video Segmentation Utilizing Memory Reduction Techniques

This paper presents the implementation of a video segmentation unit used for embedded automated video surveillance systems. Various aspects of the underlying segmentation algorithm are explored and modifications are made with potential improvements of segmentation results and hardware efficiency. In addition, to achieve real-time performance with high resolution video streams, a dedicated hardware architecture with streamlined dataflow and memory access reduction schemes are developed. The whole system is implemented on a Xilinx field-programmable gate array platform, capable of real-time segmentation with VGA resolution at 25 frames per second. Substantial memory bandwidth reduction of more than 70% is achieved by utilizing pixel locality as well as wordlength reduction. The hardware platform is intended as a real-time testbench, especially for observations of long term effects with different parameter settings.