Real-Time On-Road Vehicle Detection Combining Specific Shadow Segmentation and SVM Classification

Abstract

This paper presents a vision-based real-time vehicle detection approach. Combining segmenting the specific shadow area underneath the vehicle and using SVM-based classifier, the proposed approach is accurate and efficient for intelligent vehicle. Experiment results with test dataset from real traffic scenes on freeways and urban roads are presented to illustrate the performance of this approach.