Presentation | 2003/2/14 Recover of the motion and the shape from sequences of scaled orthographic images via autoassociative learning Jun FUJIKI, Takio KURITA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Recovering the camera motion and the object shape from multiple images with point correspondences is the fundamental and important problem in computer vision and many algorithms are presented. However, most algorithms do not work well when some data are missing. In this paper, we present a new algorithm which work well even if half of data are missing. The algorithm is based on autoassociative learning of multilayered neural network with their connecting coefficients constrained. The algorithm estimate missing data and recover the motion and the shape simultaneously. we evaluate the ability of the algorithm through experiment with synthesize data. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | structure from motion / sealed orthographic projection / Euclidean reconstruction / occlusion / autoassociative learning |
Paper # | PRMU2002-222 |
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Committee | PRMU |
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Conference Date | 2003/2/14(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Pattern Recognition and Media Understanding (PRMU) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Recover of the motion and the shape from sequences of scaled orthographic images via autoassociative learning |
Sub Title (in English) | |
Keyword(1) | structure from motion |
Keyword(2) | sealed orthographic projection |
Keyword(3) | Euclidean reconstruction |
Keyword(4) | occlusion |
Keyword(5) | autoassociative learning |
1st Author's Name | Jun FUJIKI |
1st Author's Affiliation | National Institute of Advanced Industrial Science and Technology() |
2nd Author's Name | Takio KURITA |
2nd Author's Affiliation | National Institute of Advanced Industrial Science and Technology |
Date | 2003/2/14 |
Paper # | PRMU2002-222 |
Volume (vol) | vol.102 |
Number (no) | 652 |
Page | pp.pp.- |
#Pages | 4 |
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