2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
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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 × 576) resolution data, and delivers real-time performance even on low-end mobile graphics processors.
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