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題名:Constrained Tree Search for Feature Correspondence
書刊名:師大學報
作者:陳世旺
出版日期:1993
卷期:38
頁次:頁37-64
主題關鍵詞:供元件對應限制性樹狀搜索法
原始連結:連回原系統網址new window
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  • 被引用次數被引用次數:期刊(0) 博士論文(0) 專書(0) 專書論文(0)
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  • 點閱點閱:11
     在電腦視覺領域中,常會遭遇到兩組特徵元件對應的問題。而利用條 件限制來作對應搜尋是一種處理這類問題相當有效的技術。本篇文章首先介紹一 種索引架構,可以簡化上述搜索演算法的施行。這種索引架構,主要是起因於杜 威的十進位符號觀念。同時由於我們所介紹的索引架構,搜尋演算法的行為方式 會如同數位式計數器,此種計數器可以很容易用硬體製成。本篇文章也對寫成的 演算程式作複雜度分析。由分析的結果,我們提出一種程序,可以幫助我們未選 取物體辦認時,較有效力的特徵元件及其相關的條件或限制。我們的實驗結果顯 示上述搜尋演算法以及選取程序均具有實際應用的價值。
     Constrained search is a useful technique for dealing with feature correspondence problems frequently encountered in machine vision. In this paper,an indexing scheme, inspired by the Dewey decimal notation, is proposed forsimplifying the implementation of the search algorithm. This scheme alsoenables the algorithm to be easily realized in hardware in view that the algorithm characterized by the scheme will behave like a digital counter. Throughanalyzing the complexity of the search algorithm, a process, that can be usedto select a robust subset of features and constraints for the purpose of objectrecognition, is presented. Experiments demonstrate the feasibilities of boththe algorithm and the process.
期刊論文
1.Bolles, R. C.、Cain, R. A.(1982)。Recognizing and Locating Partially Visible Objects: the Local-Feature-Focus Method。Int. J. Robotics Res.,1(3),57-82。  new window
2.陳世旺(19920600)。Computing Structural Constraints from a set of 3D Geometrical Entities。師大學報,37,267-293。new window  new window
3.Gaston, P. C.、Lozano-P'erez, T.(1984)。Model-Based Recognition and Localization from Sparse Range or Tactile Data。Int. J. Robotics Res.,3(3),3-35。  new window
4.Grimson, W. E. L.、Lozano-P'erez, T.(1984)。Tactile Recognition and Localization Using Object Models: The Case of Polyhedra on a Plane。IEEE PAMI,6(3)。  new window
5.Grimson, W. E. L.(1986)。Sensing Strategies for Disambiguating Among Multiple Objects in Known Poses。IEEE J. of Robotics and Automation,RA-2(4),196-213。  new window
6.Grimson, W. E. L.、Lozano-P'erez, T.(1987)。Localizing Overlapping Parts by Searching the Interpretation Tree。IEEE PAMI,9(4),469-482。  new window
7.Grimson, W. E. L.(1986)。The Combinatorics of Local Constraints in Model-Based Recognition and Localization from Sparse Data。Journal of the Association for Computing Machinery,33(4),658-686。  new window
8.Grimson, W. E. L.(1989)。On the Recognition of Curved Objects。IEEE PAMI,11(6),632-643。  new window
會議論文
1.Grimson, W. E. L.(1988)。The Combinatorics of Object Recognition in Cluttered Environments using Constrained Search。ICCV 2。Pampa, Horida。218-227。  new window
圖書
1.Brooks, R. A.(1984)。Model-Based Compute Vision。Ann Arbor, Michigan:UMl Research Press。  new window
2.Knuth, D. E.(1973)。The Art of Computer Programming: Volume 1. Fundamental Algorithms。Addison-Wesley Pub. Company。  new window
3.Bellman, Richard E.(1957)。Dynamic Programming。Princeton, N.J.:Princeton University Press。  new window
圖書論文
1.Fischler, M. A.、Bolles, R. C.(1981)。Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography。Graphics and Image Processing。  new window
2.Waltz, D.(1975)。Understanding Line Drawings of Scenes with Shadows。The Psychology of Computer Vision。New York:McGraw-Hill Book Comp.。  new window
 
 
 
 
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