Presentation 2006-01-12
A Multi-Directional Motion Detection Network using Population Vector Representation
Yosuke YOSHII, Takeshi NAKAYASHIKI, Masakazu KOMORI,
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Abstract(in English) In the monkey's brain, neurons which have motion direction selectivity have been found in the layer 4B of primary visual cortex. However, when detect motion direction, it is hard to think that detected direction is only with direction indicated by selectivity of one neuron. As same as visual cortex, neurons which have motion direction selectivity have been found in the motor cortex of monkey's brain. In the physiological experiment of monkey, there is result that motion direction of hand is correspond with sum of direction which is indicated by neurons respond to motion. This phenomenon is called population vector. There is a possibility that a similar thing is being done in the visual cortex. Therefore, in this study, we propose a multi-directional motion detection network using population vector representation.
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Keyword(in English) Neural Network / Visual Processing / Multi-Directional Motion Detection / Population Vector
Paper # CAS2005-80
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Committee CAS
Conference Date 2006/1/5(1days)
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Registration To Circuits and Systems (CAS)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A Multi-Directional Motion Detection Network using Population Vector Representation
Sub Title (in English)
Keyword(1) Neural Network
Keyword(2) Visual Processing
Keyword(3) Multi-Directional Motion Detection
Keyword(4) Population Vector
1st Author's Name Yosuke YOSHII
1st Author's Affiliation Department of Electrical Engineering, Miyakonojo National College of Technology()
2nd Author's Name Takeshi NAKAYASHIKI
2nd Author's Affiliation Department of Electrical Engineering, Miyakonojo National College of Technology
3rd Author's Name Masakazu KOMORI
3rd Author's Affiliation Department of Electrical Engineering, Miyakonojo National College of Technology
Date 2006-01-12
Paper # CAS2005-80
Volume (vol) vol.105
Number (no) 503
Page pp.pp.-
#Pages 6
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