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Simultaneous and fast 3D tracking of multiple faces in video by GPU-based stream processing

Oscar Mateo Lozano, Kazuhiro Otsuka
NTT Communication Science Laboratories, 3-1, Morinosato-Wakamiya, Atsugi-shi, 243-0198, Japan
IEEE International Conference on Acoustics, Speech and Signal Processing, 2008. ICASSP 2008, p.713-716

@conference{lozano2008simultaneous,

   title={Simultaneous and fast 3D tracking of multiple faces in video by GPU-based stream processing},

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

   booktitle={Acoustics, Speech and Signal Processing, 2008. ICASSP 2008. IEEE International Conference on},

   pages={713–716},

   issn={1520-6149},

   year={2008},

   organization={IEEE}

}

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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. Using stream processors for performing the computations as well as 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 technology, we can achieve real-time performance even when tracking multiple objects in high-quality videos.
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