A Novel Method for Detecting and Tracking Vehicles in Traffic-Image Sequence

摘要

A novel method for detecting and tracking vehicles is proposed. The method which based on motion object segmentation used Cellular Neural Network (CNN) in the background substraction for motion detection in order to distinguish the vehicles from others of the interested regions. Meanwhile a tracking method based on regional characteristic matching is proposed, by which the distance between characteristic vectors can be used to match current motion regions and track the vehicles. Perceptual grouping refers to the organization ability that visual system detect image features in accordance with certain cues such as proximity, continuity, closure, etc, and attracts wide attentions and high regards in computer vision. In this paper, we proposed a new approach for occlution elimination by combining perceptual grouping with Optical flow field. Experimental results show that the methods can extract traffic information with high accuracy and efficiency.