Obstacle detection based on multiple cues fusion from monocular camera

This paper presents an obstacle detection method by using a monocular camera on a moving platform. The method can detect various static and moving obstacles based on multi-cues fusion. Firstly, an improved motion compensation cue is applied to detect the obstacles which violate the road plane assumption; Secondly, a novel image segmentation cue is introduced to increase the obstacle detection rate and decrease false detection rate; Furthermore, these cues are combined in a Bayesian framework to generate a probability map of obstacle; Finally, an efficient probability update model is presented to update the probability map and the obstacle regions can be generated. Experiment results show that the proposed obstacle detection method is robust to obstacle types, varying illumination conditions, and various scenes. Moreover, using the combined cues outperforms any individual cue.