Presentation 2010-05-13
Action Recognition using ST-patch Features for First Person Vision
Takuya FURUKAWA, Hironobu FUJIYOSHI,
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Abstract(in English) Much research has been devoted in recent years to recognizing human action from video images. Most existing methods, however, take video of people from the outside making it difficult to understand behavioral intention. The First Person Vision approach has been proposed in response to this problem. In this approach, a device consisting of two cameras collectively called an "inside-out camera" is attached to the head of a person to obtain "scene video" that captures the person's visual field and "eyeball video" that observes one of the person's eyeballs. These video streams are used as a basis for understanding that person's behavioral intention. With the aim of realizing First Person Vision, we here calculate features using a global ST-patch and a local ST-patch from scene video and attempt to distinguish six types of actions while walking using Joint Boosting. Results of a comparison experiment revealed that the proposed method improved the accuracy of distinguishing actions by 27.3% compared to an optical-flow method.
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Keyword(in English) First Person Vision / Inside-Out camera / ST-patch / Joint Boosting
Paper # IE2010-23,PRMU2010-11,MI2010-11
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Committee MI
Conference Date 2010/5/6(1days)
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Registration To Medical Imaging (MI)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Action Recognition using ST-patch Features for First Person Vision
Sub Title (in English)
Keyword(1) First Person Vision
Keyword(2) Inside-Out camera
Keyword(3) ST-patch
Keyword(4) Joint Boosting
1st Author's Name Takuya FURUKAWA
1st Author's Affiliation Dept. of Computer Science, Chubu University()
2nd Author's Name Hironobu FUJIYOSHI
2nd Author's Affiliation Dept. of Computer Science, Chubu University
Date 2010-05-13
Paper # IE2010-23,PRMU2010-11,MI2010-11
Volume (vol) vol.110
Number (no) 28
Page pp.pp.-
#Pages 6
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