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Real-time Visual Tracker by Stream Processing

Oscar Mateo Lozano, Kazuhiro Otsuka
NTT Communication Science Laboratories, 3-1, Morinosato-Wakamiya, Atsugi-shi 243-0198, Japan
Journal of Signal Processing Systems, Vol. 57, No. 2. (1 November 2009), pp. 285-295.

@article{mateo2009real,

   title={Real-time visual tracker by stream processing},

   author={Mateo Lozano, O. and Otsuka, K.},

   journal={Journal of Signal Processing Systems},

   volume={57},

   number={2},

   pages={285–295},

   issn={1939-8018},

   year={2009},

   publisher={Springer}

}

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In this work, we implement a real-time visual tracker that targets the position and 3D pose of objects in video sequences, specifically faces. The use of stream processors for the computations and efficient Sparse-Template-based particle filtering allows us to achieve real-time processing even when tracking multiple objects simultaneously in high-resolution video frames. Stream processing is a relatively new computing paradigm that permits the expression and execution of data-parallel algorithms with great efficiency and minimum effort. Using a GPU (graphics processing unit, a consumer-grade stream processor) and the NVIDIA CUDA
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