Robust range image registration :using genetic algorithms and the surface interpenetration measure
- 作者: Silva, Luciano Afonso da,
- 其他作者: Bellon, Olga R. P. , Boyer, Kim L.
- 出版: Hackensack, N.J. : World Scientific ©2005.
- 稽核項: 1 online resource (x, 164 pages) :illustrations (some color).
- 叢書名: Series in machine perception and artificial intelligence ;v. 60
- 標題: COMPUTERS , Mathematical models. , Electronic book. , Electronic books. , Computer simulation. , Computer Simulation. , COMPUTERS Computer Simulation.
- ISBN: 9812561080 , 9789812561084
- 試查全文@TNUA:
- 附註: Includes bibliographical references (pages 157-162) and index. Introduction -- Range Image Registration -- Surface Interpenetration Measure (SIM) -- Range Image Registration using Genetic Algorithms -- Robust Range Registration by Combining GAs and the SIM -- Multiview Range Image Registration -- Closing Comments.
- 摘要: This book addresses the range image registration problem for automatic 3D model construction. The focus is on obtaining highly precise alignments between different view pairs of the same object to avoid 3D model distortions; in contrast to most prior work, the view pairs may exhibit relatively little overlap and need not be prealigned.
- 電子資源: https://dbs.tnua.edu.tw/login?url=https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=126926
- 系統號: 005314853
- 資料類型: 電子書
- 讀者標籤: 需登入
- 引用網址: 複製連結
- Provides a comprehensive review of the literature in range image registration and serves as an effective study guide on this important topic - Presents a novel robust error measure, the surface interpretation, which is easily computed and offers significant immunity to non-Gaussian errors. The shortcomings of the least squares formalism in this setting are carefully explored - The first substantive work focusing on precision alignment, and the first capable of attaining such alignments in low-overlap scenarios without human intervention or manual prealignment - Offers extensive experimental results, highlighting both the impact of robust measures, and the relative efficiency of genetic search algorithms versus more traditional approaches. Extensive comparisons with more traditional algorithms and measures are presented
來源: Google Book
來源: Google Book
評分
