Fast gain-adaptive KLT tracking on the GPU
University of North Carolina, Chapel Hill, NC
IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2008. CVPRW ’08
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.
May 12, 2011 by hgpu
