Automotive Tracking with High-speed Stereo Vision Based on a Spatiotemporal Shared Filter

Abstract

In this study, we propose a robust method for automotive tracking using high-speed stereo vision. The tracking is achieved using a shared correlation filter for stereo images that can be captured at high speed using the features of high-framerate images. In addition, by adjusting the tracking window for each automobile, robust tracking can be performed even in the case of partial occlusion with respect to visually overlapping automobiles. Experiments on in-vehicle camera images were performed at a frame rate of 500 fps to validate the efficacy of the proposed approach.