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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Proceedings ArticleDOI
A model-based method for object recognition
TL;DR: A method is presented for using the high-level descriptions of objects (i.e. their models) to recognize them in an image to detect and recognize partially occluded and camouflaged objects.
Proceedings ArticleDOI
Taxonomy and procedures for adaptive autonomous systems in crowded hybrid environments
TL;DR: The focus in the paper is on taxonomy of humans displacement and on the use of the personal space notion in planning the robot movements.
Journal ArticleDOI
A CAD Model Based System for Object Recognition
TL;DR: This paper proposes a scheme for interfacing the CAD database of objects and the computer vision processes used for recognising these objects.
Journal ArticleDOI
Shape understanding system: understanding of the complex object
Zbigniew Les,Magdalena Les +1 more
TL;DR: The main novelty of the presented method is that the process of understanding is related to the visual concept represented as a symbolic name of the possible class of shapes of the shape understanding system.
Book ChapterDOI
Object Recognition and Performance Bounds
Jake K. Aggarwal,Shishir K. Shah +1 more
TL;DR: The paper discusses the Bayesian paradigm and contrasts its ability to provide performance bounds as compared to neural networks and rule based systems and future direction of results on object recognition and performance bounds will also be discussed.
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.