MISC

査読有り
2011年

Versatile Neural Network Method for Recovering Shape from Shading by Model Inclusive Learning

2011 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN)
  • Yasuaki Kuroe
  • ,
  • Hajimu Kawakami

開始ページ
3194
終了ページ
3199
記述言語
英語
掲載種別
DOI
10.1109/IJCNN.2011.6033644
出版者・発行元
IEEE

The problem of recovering shape from shading is important in computer vision and robotics. In this paper, we propose a versatile method of solving the problem by neural networks. We introduce a mathematical model, which we call 'image-formation model', expressing the process that the image is formed from an object surface. We formulate the problem as a model inclusive learning problem of neural networks and propose a method to solve it. In the proposed learning method, the image-formation model is included in the learning loop of neural networks. The proposed method is versatile in the sense that it can solve the problem in various circumstances. The effectiveness of the proposed method is shown through experiments performed in various circumstances.

リンク情報
DOI
https://doi.org/10.1109/IJCNN.2011.6033644
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000297541203048&DestApp=WOS_CPL
ID情報
  • DOI : 10.1109/IJCNN.2011.6033644
  • Web of Science ID : WOS:000297541203048

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