Efficient stereo matching for moving cameras and decalibrated rigs

Abstract

Abstract-In vehicular applications based on motion-stereo using monocular side-looking cameras, pairs of images must usually be rectified very well, to allow the application of dense stereo methods. But also long-term installations of stereo rigs in vehicles require approaches that cope with the decalibration of the cameras. The need for such methods is further underlined by the fact that offline camera calibration is a costly and timeconsuming procedure at vehicle production sites.In this paper we propose an approach for dense stereo matching that overcomes issues arising from inaccurately rectified images. For this, we significantly increase the search range for correspondences, but still preserve a high efficiency of the method to allow operation on platforms with highly limited processing resources.We demonstrate the performance of our ideas quantitatively using well known stereo datasets and qualitatively using real video sequences of a motion-stereo application.

Motorcycles that See: Multifocal Stereo Vision Sensor for Advanced Safety Systems in Tilting Vehicles

“…In these cases, the stereo frame is generated for a monocular moving camera, which moves over a rigid scene. The main assumption of this technique is a small vertical displacement, and consequently the matching strategy is relaxed by exploring a corridor around the epipolar line [ 81 ].…”