Detection of moving objects in image plane for robot navigation using monocular vision

Abstract

This article presents an algorithm for moving object detection (MOD) in robot visual simultaneous localization and mapping (SLAM). This MOD algorithm is designed based on the defining epipolar constraint for the corresponding feature points on image plane. An essential matrix obtained using the state estimator is utilized to represent the epipolar constraint. Meanwhile, the method of speeded-up robust feature (SURF) is employed in the algorithm to provide a robust detection for image features as well as a better description of landmarks and of moving objects in visual SLAM system. Experiments are carried out on a hand-held monocular camera to verify the performances of the proposed algorithm. The results show that the integration of MOD and SURF is efficient for robot navigating in dynamic environments. Keywords: simultaneous localization, and mapping (SLAM), moving object detection (MOD), moving object tracking (MOT), speeded-up robust features (SURF), monocular vision © 2012 Wang et al.