Occupant Detection through Near-Infrared Imaging
Xiaoli Hao, Houjin Chen, Yongyi Yang, Chang Yao, Heng Yang, Na Yang · Journal of Applied Science and Engineering · 2011
This paper investigates a method to detect and count occupants in vehicles, the purpose of which is to facilitate the task of monitoring and counting of vehicle occupants either by human screeners or by pattern recognition algorithms. The proposed near-infrared (NIR) imaging method can effectively deal with the challenge due to poor light conditions, windshield reflection, tinted windows and shadows on windshields to improve the clarity of the captured image of the vehicle interior. We also proposed an algorithm to process the NIR images. Firstly, the vehicle windshield region was extracted based on optimal edge detections and Hough transform, and 60 line detector masks and integral projection. Then, the occupants’ faces in the region were segmented through AdaBoost-based face detection. Experimental results show that the method has the potential possibility to automatically detect vehicle occupants.