Presentation	1997/6/19 Visual Learnign and Prediction of Motion Patterns Tadashi Ogawa, Hiroshi Ando,
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Abstract(in English)	We studied Elman-type recurrent neural networks for predicting and classifying spatio-temporal visual patterns. Computer experiments, using the complex temporal data of human arm movements, demonstrated that the network model has the following abilities; 1)short-term prediction, 2)long-term prediction, 3)motion pattern classification, 4)view generalization, 5)learning multiple patterns from different, viewpoints, and 6)temporal adaptation for time scaling.
Keyword(in Japanese)	(See Japanese page)
Keyword(in English)	recurrent neural networks / view generalization / spatio-temporal prediction / motion pattern classification / temporal adaptation
Paper #	NC97-22
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Conference Information
Committee	NC
Conference Date	1997/6/19(1days)
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Paper Information
Registration To	Neurocomputing (NC)
Language	JPN
Title (in Japanese)	(See Japanese page)
Sub Title (in Japanese)	(See Japanese page)
Title (in English)	Visual Learnign and Prediction of Motion Patterns
Sub Title (in English)
Keyword(1)	recurrent neural networks
Keyword(2)	view generalization
Keyword(3)	spatio-temporal prediction
Keyword(4)	motion pattern classification
Keyword(5)	temporal adaptation
1st Author's Name	Tadashi Ogawa
1st Author's Affiliation	Graduate School of Information Science, Nara Institute of Science and Technology()
2nd Author's Name	Hiroshi Ando
2nd Author's Affiliation	ATR Human Information Processing Research Laboratories
Date	1997/6/19
Paper #	NC97-22
Volume (vol)	vol.97
Number (no)	116
Page	pp.pp.-
#Pages	8
Date of Issue