Presentation 2010-09-05
Improvement in Human Detection by Generation Addition Training of Human Silhouette
Naoya KOUKETSU, Yuji YAMAUCHI, Hironobu FUJIYOSHI,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) An object detection method that involves additional learning with a training sample generated by a 3-D human model is proposed. In general human detection, the environment collection of the training sample may differ greatly from the detection environment, resulting in low detection accuracy. In the proposed method, a general classifier is learned in advance, and then camera position, a background image, and other such information on the detection environment is input to generate training samples that are specialized for that environment for use in additional training. That makes it possible to learn a final classifier that is specific to a particular environment. The results of evaluation experiments show that the proposed method increased the detection rate by 13.8% relative to a training method that used the INRIA Person Dataset, with a FPPW of 0.01.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Human detection / Generation addition training / Human silhouette
Paper # PRMU2010-70,IBISML2010-42
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Conference Information
Committee PRMU
Conference Date 2010/8/29(1days)
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Paper Information
Registration To Pattern Recognition and Media Understanding (PRMU)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Improvement in Human Detection by Generation Addition Training of Human Silhouette
Sub Title (in English)
Keyword(1) Human detection
Keyword(2) Generation addition training
Keyword(3) Human silhouette
1st Author's Name Naoya KOUKETSU
1st Author's Affiliation Chubu University()
2nd Author's Name Yuji YAMAUCHI
2nd Author's Affiliation Chubu University
3rd Author's Name Hironobu FUJIYOSHI
3rd Author's Affiliation Chubu University
Date 2010-09-05
Paper # PRMU2010-70,IBISML2010-42
Volume (vol) vol.110
Number (no) 187
Page pp.pp.-
#Pages 6
Date of Issue