Abstract-In this paper, an FPGA based mobile feature detection and tracking solution is proposed for complex video processing systems. Presented algorithms include feature (corner) detection and robust memory allocation solution to track in real-time corners using the extended Kalman filter. Target implementation environment is a Xilinx Zynq SoC FPGA based. Using the HW/SW partitioning flexibility of Zynq, the ARM dual core processor performance and hardware accelerators generated by Xilinx SDSOC and Vivado HLS tools improve the system ability of processing video accurately with a high frame rate. Several original innovations allow to improve the processing time of the whole system (detection and tracking) by 50% as shown in experimental validation (tracking of visually impaired during their outdoor navigation).
Abdelkader et al. REF implemented an embedded architecture for corner detection and tracking system in video sequence, using the HW/SW partitioning flexibility of Zynq platform.
Zynq FPGA based and Optimized Design of Points of Interest Detection and Tracking in Moving Images for Mobility System
International Journal of Advanced Computer Science and Applications
Computer Science