Real-time Feature Tracking on an Embedded Vision Sensor for Small Vision-guided Unmanned Vehicles

Abstract

Small unmanned vehicles (UVs) are seeing more widespread use In military, scientific, and civil sectors in recent years. Because of the limitations inherent in small UVs, including power consumption and payload, the selection of light weight and low power sensors and processors becomes critical. Low power CMOS cameras and real-time vision processing algorithms can provide fast and reliable information to the UVs. These vision algorithms often require computational power that limits their use in traditional general purpose processors using conventional software. The latest developments in field programmable gate arrays (FPGAs) provide an alternative for hardware and software co-design of complicated real-time vision algorithms. Many vision algorithms utilize image features as the main source of information. By tracking features from one frame to another, it becomes possible to perform many different high-level vision tasks. This paper describes a feature tracking algorithm and an FPGA hardware implementation that operates in real-time.