Journal ArticleDOI
Model-based recognition in robot vision
Roland T. Chin,Charles R. Dyer +1 more
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TLDR
This paper presents a comparative study and survey of model-based object-recognition algorithms for robot vision, and an evaluation and comparison of existing industrial part- recognition systems and algorithms is given, providing insights for progress toward future robot vision systems.Abstract:
This paper presents a comparative study and survey of model-based object-recognition algorithms for robot vision. The goal of these algorithms is to recognize the identity, position, and orientation of randomly oriented industrial parts. In one form this is commonly referred to as the "bin-picking" problem, in which the parts to be recognized are presented in a jumbled bin. The paper is organized according to 2-D, 2½-D, and 3-D object representations, which are used as the basis for the recognition algorithms. Three central issues common to each category, namely, feature extraction, modeling, and matching, are examined in detail. An evaluation and comparison of existing industrial part-recognition systems and algorithms is given, providing insights for progress toward future robot vision systems.read more
Citations
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Book ChapterDOI
Efficient query processing with compiled knowledge bases
Neil V. Murray,Erik Rosenthal +1 more
TL;DR: A target for knowledge compilation called the ri-trie is introduced; it has the property that even if they are large they nevertheless admit fast queries, so that a query can be processed in time linear in the size of the query regardless of thesize of the compiled knowledge base.
Book ChapterDOI
Point Probe Decision Trees for Geometric Concept Classes
Esther M. Arkin,Michael T. Goodrich,Joseph S. B. Mitchell,David M. Mount,Christine D. Piatko,Steven Skiena +5 more
TL;DR: This work studies the problem of computing efficient strategies (“decision trees”) for probing an image and proves a hardness result and gives strategies that obtain decision trees whose height is within a log factor of optimal.
Proceedings ArticleDOI
Bayesian view class determination
A. Pathak,Octavia Camps +1 more
TL;DR: A Bayesian approach to the view class determination problem is presented and it is suggested that different definitions of clustering should be studied.
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Shape understanding system: understanding a convex object
Zbigniew Les,Magdalena Les +1 more
TL;DR: The main novelty of the presented method is that the process of understanding a convex object is related to the visual concept represented as a symbolic name of the possible classes of shapes.
Journal ArticleDOI
3D object perception using gradient descent
Leemon Baird,Patrick S. P. Wang +1 more
TL;DR: Experimental results on various line drawing objects show that this gradient descent algorithmrunning on a Macintosh II is one to two orders of magnitude faster than the MSDA algorithm running on a Symbolics, while still giving comparable results.
References
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Journal ArticleDOI
Generalizing the hough transform to detect arbitrary shapes
TL;DR: It is shown how the boundaries of an arbitrary non-analytic shape can be used to construct a mapping between image space and Hough transform space, which makes the generalized Houghtransform a kind of universal transform which can beused to find arbitrarily complex shapes.
Book
Robot Vision
TL;DR: Robot Vision as discussed by the authors is a broad overview of the field of computer vision, using a consistent notation based on a detailed understanding of the image formation process, which can provide a useful and current reference for professionals working in the fields of machine vision, image processing, and pattern recognition.
Journal ArticleDOI
Fourier Descriptors for Plane Closed Curves
Charles T. Zahn,Ralph Roskies +1 more
TL;DR: It is established that the Fourier series expansion is optimal and unique with respect to obtaining coefficients insensitive to starting point and the amplitudes are pure form invariants as well as are certain simple functions of phase angles.