GPU ACCELERATED REAL-TIME OBJECT DETECTION ON HIGH RESOLUTION VIDEOS USING MODIFIED CENSUS TRANSFORM

Abstract

This paper presents a novel GPU accelerated object detection system using CUDA. Because of its detection accuracy, speed and robustness to illumination variations, a boosting based approach with Modified Census Transform features is used. Results are given on the face detection problem for evaluation. Results show that even our single-GPU implementation can run in real-time on high resolution video streams without sacrificing accuracy and outperforms the single-threaded and multi-threaded CPU implementations for resolutions ranging from 640×480 to 1920×1080 by a factor of 12-18x and 4-6x, respectively.