Title :
Fast gain-adaptive KLT tracking on the GPU
Author :
Zach, Christopher ; Gallup, David ; Frahm, Jan-Michael
Author_Institution :
North Carolina Univ., Chapel Hill, NC
Abstract :
High-performance feature tracking from video input is a valuable tool in many computer vision techniques and mixed reality applications. This work presents a refined and substantially accelerated approach to KLT feature tracking performed on the GPU. Additionally, a global gain ratio between successive frames is estimated to compensate for changes in the camera exposure. The proposed approach achieves more than 200 frames per second on state-of-the art consumer GPUs for PAL (720 times 576) resolution data, and delivers real-time performance even on low-end mobile graphics processors.
Keywords :
feature extraction; image processing equipment; image resolution; GPU; KLT feature tracking; global gain ratio; graphics processing unit; video input; Acceleration; Application software; Cameras; Computer vision; Graphics; Hardware; Karhunen-Loeve transforms; Pixel; Runtime; Virtual reality;
Conference_Titel :
Computer Vision and Pattern Recognition Workshops, 2008. CVPRW '08. IEEE Computer Society Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
978-1-4244-2339-2
Electronic_ISBN :
2160-7508
DOI :
10.1109/CVPRW.2008.4563089