Journal ArticleDOI
Model-based recognition in robot vision
Roland T. Chin,Charles R. Dyer +1 more
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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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Journal ArticleDOI
A method for registration of 3-D shapes
Paul J. Besl,H.D. McKay +1 more
TL;DR: In this paper, the authors describe a general-purpose representation-independent method for the accurate and computationally efficient registration of 3D shapes including free-form curves and surfaces, based on the iterative closest point (ICP) algorithm, which requires only a procedure to find the closest point on a geometric entity to a given point.
Journal ArticleDOI
Comparing images using the Hausdorff distance
TL;DR: Efficient algorithms for computing the Hausdorff distance between all possible relative positions of a binary image and a model are presented and it is shown that the method extends naturally to the problem of comparing a portion of a model against an image.
Journal ArticleDOI
Neural network-based face detection
TL;DR: A neural network-based upright frontal face detection system that arbitrates between multiple networks to improve performance over a single network, and a straightforward procedure for aligning positive face examples for training.
Journal ArticleDOI
Alignment by Maximization of Mutual Information
Paul A. Viola,William M. Wells +1 more
TL;DR: A new information-theoretic approach is presented for finding the pose of an object in an image that works well in domains where edge or gradient-magnitude based methods have difficulty, yet it is more robust than traditional correlation.
Proceedings ArticleDOI
Method for registration of 3-D shapes
Paul J. Besl,Neil David Mckay +1 more
TL;DR: In this paper, the authors describe a general purpose representation independent method for the accurate and computationally efficient registration of 3D shapes including free-form curves and surfaces, based on the iterative closest point (ICP) algorithm, which requires only a procedure to find the closest point on a geometric entity to a given point.
References
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TL;DR: In this paper, the orientation of patches on the surface of an object can be determined from multiple images taken with different illumination, but from the same viewing position, using table lookup based on numerical inversion of reflectance maps.
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Journal ArticleDOI
A Model-Based Vision System for Industrial Parts
TL;DR: A vision system has been developed which can determine the position and orientation of complex curved objects in gray-level noisy scenes and organizes and reduces the image data from a digitized picture to a compact representation having the appearance of a line drawing.