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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Object recognition by affine invariant matching
TL;DR: Novel techniques are described for model-based recognition of 3-D objects from unknown viewpoints using single-gray-scale images and efficient matching algorithms are proposed, which assume affine approximation to the perspective viewing transformation.
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Deformable template models: a review
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3-D shape recovery using distributed aspect matching
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Proceedings ArticleDOI
Learning and recognition of 3D objects from appearance
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TL;DR: The authors address the problem of automatically learning object models for recognition and pose estimation as one of matching visual appearance rather than shape and present a new compact representation of object appearance that is parameterized by pose and illumination.
BookDOI
Curvature Scale Space Representation: Theory, Applications, and MPEG-7 Standardization
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TL;DR: Curvature Scale Space Representation: Theory, Applications, and MPEG-7 Standardization is based on key publications on the CSS technique, as well as its multiple applications and generalizations, to ensure that the reader will have access to the most fundamental results concerning the CSS method in one volume.
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.