Evaluation of Moving Object Segmentation Comparing 6D-Vision and Monocular Motion Constraints

Abstract

Detecting moving objects is a very important aspect of driver assistance systems (DAS). This paper handles this issue by using a vision based system mounted within the vehicle. The pipeline for both a stereoscopic and monocular approach are covered. Both approaches use image sequences and compare moving feature points over time. This sparse information is then segmented using the optimal graph-cut algorithm, by also incorporating the grey-scale images. This paper then evaluates and contrasts the two approaches to identify the accuracy and robustness of each approach. The two methods both work in real-time on normal PC hardware (Quad Core CPU).