Presentation 2013-11-23
Brain-style image recognition algorithm constructed from the human brain activity at higher visual cortices : Application to the recognition of occluded pedestrian images
Hiroyuki HOSHINO, Takashi OWAKI, Hiroki KURASHIGE, Kenichi UENO, Topi TANSKANEN, Kang CHENG, Hideyuki CATEAU,
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Abstract(in English) The purpose of our study is to improve the robustness of image recognition for pedestrians or vehicles occluded by other objects. Previously, we developed a method of constructing a brain-style visual recognition algorithm from multi-neuron activity data. In this paper, we apply the method to the human brain activity at the higher visual cortices measured by fMRI, and show that our algorithm is improved in the recognition of occluded pedestrian images.
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Keyword(in English) image recognition / higher visual cortex / fMRI / kernel canonical correlation analysis / pedestrian detection / occlusion
Paper # NC2013-52
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Committee NC
Conference Date 2013/11/15(1days)
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Registration To Neurocomputing (NC)
Language JPN
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Title (in English) Brain-style image recognition algorithm constructed from the human brain activity at higher visual cortices : Application to the recognition of occluded pedestrian images
Sub Title (in English)
Keyword(1) image recognition
Keyword(2) higher visual cortex
Keyword(3) fMRI
Keyword(4) kernel canonical correlation analysis
Keyword(5) pedestrian detection
Keyword(6) occlusion
1st Author's Name Hiroyuki HOSHINO
1st Author's Affiliation Toyota Central R&D Labs, Inc.()
2nd Author's Name Takashi OWAKI
2nd Author's Affiliation Toyota Central R&D Labs, Inc.
3rd Author's Name Hiroki KURASHIGE
3rd Author's Affiliation RIKEN BSI-TOYOTA Collaboration Center, RIKEN
4th Author's Name Kenichi UENO
4th Author's Affiliation RIKEN BSI, RIKEN
5th Author's Name Topi TANSKANEN
5th Author's Affiliation RIKEN BSI, RIKEN
6th Author's Name Kang CHENG
6th Author's Affiliation RIKEN BSI, RIKEN
7th Author's Name Hideyuki CATEAU
7th Author's Affiliation RIKEN BSI-TOYOTA Collaboration Center, RIKEN
Date 2013-11-23
Paper # NC2013-52
Volume (vol) vol.113
Number (no) 315
Page pp.pp.-
#Pages 6
Date of Issue