Real-Time SURF-Based Video Stabilization System for an FPGA-Driven Mobile Robot

Abstract

Mobile robots are used for search and rescue purposes in emergency informatics. The robots typically carry a vision system to gather information about the environment and pass on to remotely located rescue teams. When the robot moves, in view of the uneven nature of the terrain, the camera is subjected to vibrations and as a result, the transmitted videos tend to be unclear. Further, real-time data collection and processing are critical for quick action by rescue personnel. In this paper, we explore a robust and high-performance approach for video stabilization. In particular, we develop a systolic array for interest point detection and description, key phases in the speeded-up robust features (SURF) approach for finding point correspondences between two images of a scene. The systolic array is then used as part of a pipelined architecture for video stabilization. The entire architecture is ported on to a field-programmable gate array (FPGA) for real-time video stabilization on a mobile robot. Experiments with the FPGA-driven robot in our laboratory and institute corridors validate the efficacy of the proposed strategy.