2P1-D20 GPU accelerating visual tracking

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概要

• 論文の詳細を見る

• This paper describes our novel work of using graphic processing unit (GPU) on visual tracking. In this paper, we present our novel implementations of GPU based Efficient Second-order Minimization (GPU-ESM) algorithm. By utilizing the tremendous parallel processing capability of modern graphic hardware, we obtain significant processing acceleration from GPU over its CPU counterpart. Currently our GPU-ESM algorithm can process tracking area of 360×360 pixels at 145 fps on NVIDIA GTX295 board and Intel Core i7 920, which is approximately 30 times faster than CPU implementation. This speedup substantially improves the realtime performance of our system. In this paper, translation details of ESM algorithm from CPU to GPU implementation and novel optimizations are presented. The effectiveness of our GPU-ESM tracking algorithm is validated with experimental data.

• 一般社団法人日本機械学会の論文

著者

• HASHIMOTO Koichi

  Tohoku University

• ZANG Chuantao

  Tohoku University

• ENDO Yoshihide

  Tohoku University

関連論文

• 2P2-B24 Illumination-based Synchronization of High-Speed Vision Sensors
• 2P1-D20 GPU accelerating visual tracking
• 2P2-B18 2D tracking of single micro-organism based on parallel level set method with intensity constraint

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