Abstract:
Pedestrian detection is one of the most challenging and vital tasks of driver assistance systems (DAS). Among several algorithms devel- oped for human detection, histogram of oriented gradients (HOG) followed by support vector machine (SVM) has shown the most promising results. This paper presents a hardware accelerator for real-time pedestrian detection at di erent scales to ful ll the real- time requirements of DAS. It proposes an algorithmic modi ca- tion to the conventional multi-scale object detection by means of HOG+SVM to increase the throughput and maintain the accuracy reasonably high. Our hardware accelerator detects pedestrians at the rate of 60 fps for HDTV (1080x1920) frame.