Proceedings ArticleDOI
Vertex space analysis and its application to model based object recognition
G. Whitten
- pp 847-857
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TLDR
The author discusses some of the properties of vertex space, including insensitivity to changes in scale, orientation, and partial object occlusion, and how these properties relate to problems in model-based object recognition.Abstract:
The author discusses some of the properties of vertex space, including insensitivity to changes in scale, orientation, and partial object occlusion, and how these properties relate to problems in model-based object recognition. He also describes techniques developed for 2-D and 3-D object recognition using vertex space. The vertex-space approach to object recognition is powerful and efficient, deals well with missing information, and does not require conventional region segmentation. Results to date and an indication of future research directions are presented. >read more
Citations
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A control point matching algorithm
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References
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TL;DR: The theory of edge detection explains several basic psychophysical findings, and the operation of forming oriented zero-crossing segments from the output of centre-surround ∇2G filters acting on the image forms the basis for a physiological model of simple cells.
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On seeing things
TL;DR: It is argued that at least two types of description of the pattern must be utilised if any significant pattern generalisation is to be achieved, and in general that all picture interpretation tasks involve descriptions in two domains.
Generating Semantic Descriptions From Drawings of Scenes With Shadows
TL;DR: This report reproduces a thesis of the same title submitted to the Department of Electrical Engineering, Massachusetts Institute of Technology, in partial fulfillment of the requirements for the degree of Doctor of Philosophy, September 1972.
Book ChapterDOI
A Graph-Theoretic Approach to 3-D Object Recognition and Estimation of Position and Orientation
Edward K. Wong,K. S. Fu +1 more
TL;DR: This paper describes a new technique for modeling and recognition of 3-D objects that satisfies the constraints at the node of the model graph matched and techniques are described for the estimation of position and orientation.