3D objects reconstruction from single 2D graph based on neural networks - Details

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Abstract：

A　system　scheme　was　presented　in　this　paper,　which　could　be　used　in　3D　objects　reconstruction　from　single　2D　sketch.　Corner　points　and　several　other　structural　features　were　adopted　in　this　system.　BP　neural　network　was　also　applied　due　to　its　non-linear　mapping　and　feature　extracting　ability.　In　order　to　obtain　the　corner　points　more　effectively,　an　adaptive　corner　detection　algorithm　was　proposed　based　on　curvature　and　slide　windows.　Experimental　results　show　that　the　selected　features　and　the　algorithm　have　superiority　in　3D　objects　reconstruction.

Keyword：

Feature extraction Edge detection Image reconstruction Backpropagation Graphic methods Neural networks

Author Community：

[ 1 ] [Sun, Guang-Min]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China
[ 2 ] [Xu, Lei]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China
[ 3 ] [Chen, De-Ming]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China
[ 4 ] [Wang, Chun]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China
[ 5 ] [Li, Gang]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China
[ 6 ] [Wang, Jing]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China

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Source ：

Journal of Beijing University of Technology

ISSN： 0254-0037

Year： 2009

Issue： 8

Volume： 35

Page： 1033-1038

Cited Count：

WoS CC Cited Count：

SCOPUS Cited Count：

ESI Highly Cited Papers on the List： 0 Unfold All

WanFang Cited Count：

Chinese Cited Count：

30 Days PV： 7

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信息科学技术学院本学院/部未明确归属的数据

材料科学与工程学院本学院/部未明确归属的数据

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