Vehicle target detection methods based on color fusion deformable part model

Abstract

Abstract In this paper, the traditional vehicle target detection method is improved, and a vehicle target detection method based on color fusion deformable part model (DPM) is proposed. Firstly, the traffic image is conducted with HSI color space conversion, and then, the information of each channel in color space is extracted, the DPM of each channel is trained, and then the color fusion DPM is obtained by using the adaptive fusion method. In the process of vehicle detection, traversal search of vehicle images is conducted using color fusion DPM through the sliding window traversal; areas with a score exceeding the threshold are deemed as the vehicle targets. In the experimental phase, we first trained the color fusion DPM, then validated the validity and accuracy, and the experiment images were from the practical traffic junctions. The results show that the method proposed in this paper can carry out vehicle target detection accurately and effectively. Compared with other vehicle target detection methods, it has high detection rate and low false positive rate, which can achieve the accurate detection of vehicle targets in intelligent transportation.

Keywords

• Color fusion DPM
• Vehicle detection
• HSI
• Intelligent transportation