Pedestrian detection is one of the most challenging and vital tasks of driver assistance systems (DAS). Among several algorithms developed 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 different scales to fulfill the real-time requirements of DAS. It proposes an algorithmic modification 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 (1080×1920) frame.
Financed by the National Centre for Research and Development under grant No. SP/I/1/77065/10 by the strategic scientific research and experimental development program:
SYNAT - “Interdisciplinary System for Interactive Scientific and Scientific-Technical Information”.