Presentation 2007-09-04
A Fast Near Neighbor Search Metric For Online Example-Based Human Pose Estimation
YUICHI SAGAWA, MASAMICHI SHIMOSAKA, TAKETOSHI MORI, TOMOMASA SATO,
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Abstract(in English) We have been working on a marker-less motion capture system that works in a multiple camera environment. This system assumes 3D voxel data to be the input, while discrete human posture data is assumed to be the output. The discreteness of human posture data is provided by an example-based approach, which constructs human posture candidates from a large motion capture database beforehand. During the estimation process, the most appropriate candidate will be chosen through a simple similarity calculation between voxel data and posture candidates. This approach will drastically reduce the computational cost. compared to conventional methods, but increase of candidates will possibly lead to considerable computational cost. Therefore, prior to the similarity calculation phase, we introduce a near-neighbor search metric, which drastically decreases the similarity caculation frequency and the total computational cost. In this paper, we present a novel near-neighbor search metric, which is capable of dealing with much more candidates than the metric presented before, and yet maintaining the speed needed for online processing.
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Paper # PRMU2007-84,HIP2007-93
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Conference Information
Committee PRMU
Conference Date 2007/8/27(1days)
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Registration To Pattern Recognition and Media Understanding (PRMU)
Language JPN
Title (in Japanese) (See Japanese page)
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Title (in English) A Fast Near Neighbor Search Metric For Online Example-Based Human Pose Estimation
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1st Author's Name YUICHI SAGAWA
1st Author's Affiliation University of Tokyo()
2nd Author's Name MASAMICHI SHIMOSAKA
2nd Author's Affiliation University of Tokyo
3rd Author's Name TAKETOSHI MORI
3rd Author's Affiliation University of Tokyo
4th Author's Name TOMOMASA SATO
4th Author's Affiliation University of Tokyo
Date 2007-09-04
Paper # PRMU2007-84,HIP2007-93
Volume (vol) vol.107
Number (no) 206
Page pp.pp.-
#Pages 8
Date of Issue