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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Design guidelines for map-based human–robot interfaces: A colocated workspace perspective
TL;DR: In this paper, the authors explored a situation where human operators direct a robot to a particular place within a limited workspace using a handheld device and found that a successful map representation would have significant benefits for the human operator's awareness of both the task and the work environment.
Journal ArticleDOI
Methods for numerical integration of high-dimensional posterior densities with application to statistical image models
TL;DR: This paper surveys previous literature and presents efficient methods for computing marginal density values for image models that have been widely considered in computer vision and image processing.
Discriminative distance measures for object detection
TL;DR: A detection framework whose core component is a nearest neighbor search over object parts, and a model for the optimal distance measure that combines the discriminative powers of more elementary distance measures associated with a collection of simple feature spaces that are easy and efficient to implement is sought.
Journal ArticleDOI
Image search using trained flexible shape models
TL;DR: A technique for building compact models of the shape and appearance of flexible objects seen in two-dimensional images derived from the statistics of sets of images of example objects with ‘landmark’ points labelled on each object is described.
A software environment for image interpretation
TL;DR: The relatable-object concept is used to determine whether the relationship exists but no relation object is instantiated to keep track of computed relations, so it is not really necessary to store such relations.
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.