A Resource-Efficient and High-Performance Implementation of Object Tracking on a Programmable System-on-Chip

Abstract: The computer vision problem of object tracking is introduced and explained. An approach to interest point based feature detection and tracking using FAST and BRIEF is presented and the selection of algorithms suitable for implementation on a Xilinx Zynq7000 with an XC7Z020 field-programmable gate array (FPGA) is detailed. A modification to the smoothing strategy of BRIEF which significantly reduces memory utilization on the FPGA is presented and benchmarked against a reference strategy. Measures of performance and resource efficiency are presented and utilized in an iterative development process. A system for interest point based object tracking that uses FAST for feature detection and BRIEF for feature description with the proposed smoothing modification is implemented on the FPGA. The design is described and important design choices are discussed.