Recognition of occluded objects with heuristic search
TL;DR: A new heuristic search based approach for recognition of partially obscured planar shapes using an admissible heuristic function which is not dependent upon the features actually used for representing the shapes.
About: This article is published in Pattern Recognition.The article was published on 1990-07-01. It has received 14 citations till now. The article focuses on the topics: Admissible heuristic & Incremental heuristic search.
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TL;DR: A robust local feature matching scheme for recognition of occluded objects that is computation efficient and can handle the nonlinear distorted local features is developed and reported.
9 citations
TL;DR: Experimental results have shown that the proposed ANN approach succeeds in recognizing isolated objects, and achieves significant gain, in number of matches, over traditional model-based object recognition systems for identifying overlapping objects.
9 citations
Cites background from "Recognition of occluded objects wit..."
..., 1988), distance transformation (Liu and Srinath, 1990), state-space search (Chaudhury et al., 1990), and generalized Hough transform (Davies, 1989; Ballard, 1981)....
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TL;DR: In this paper, a vision system which can recognize overlapping parts even though they may be partially overlapped and in random positions is proposed to identify overlapping parts in a robotic assembly task.
Abstract: The problem of recognising overlapping parts is of considerable interest in industrial automation While it is possible to employ carriers or pallets to separate or prearrange the parts for robotic assembly tasks, a vision system which can recognise the parts even though they may be partially overlapped and in random positions is much flexible
8 citations
Cites methods from "Recognition of occluded objects wit..."
...In [10], the segments obtained from the polygonal approximation of the object boundaries are used as the feature primitives....
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11 Mar 1994
TL;DR: Investigations have been carried out for finding the suitability of texture in segmentation in the case of occluded object scene and two Bayesian classifiers and one linear discriminant space classifier were designed and their success rates in identifying the manufacturing process are reported.
Abstract: The surfaces generated by different manufacturing processes like shaping, grinding, spark erosion, and casting result in textures characteristic to the machining process. Investigations have been carried out for finding the suitability of texture in segmentation in the case of occluded object scene. The specimens are prepared under controlled conditions and their digitized pictures are recorded with suitable lighting arrangement. A number of texture parameters based on first-order and second- order statistics are evaluated from these digitized images along four directions. Optimum features were selected based on interclass and intraclass scatters. Two Bayesian classifiers and one linear discriminant space classifier were designed and their success rates in identifying the manufacturing process are reported.
3 citations
References
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Book•
01 Jan 1980TL;DR: This classic introduction to artificial intelligence describes fundamental AI ideas that underlie applications such as natural language processing, automatic programming, robotics, machine vision, automatic theorem proving, and intelligent data retrieval.
Abstract: A classic introduction to artificial intelligence intended to bridge the gap between theory and practice, "Principles of Artificial Intelligence" describes fundamental AI ideas that underlie applications such as natural language processing, automatic programming, robotics, machine vision, automatic theorem proving, and intelligent data retrieval. Rather than focusing on the subject matter of the applications, the book is organized around general computational concepts involving the kinds of data structures used, the types of operations performed on the data structures, and the properties of the control strategies used. "Principles of Artificial Intelligence"evolved from the author's courses and seminars at Stanford University and University of Massachusetts, Amherst, and is suitable for text use in a senior or graduate AI course, or for individual study.
3,754 citations
TL;DR: 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.
656 citations
TL;DR: A new fast algorithm is proposed which allows for a variable number of segments iniecewise approximation as a way of feature extraction, data compaction, and noise filtering of boundaries of regions of pictures and waveforms.
Abstract: Piecewise approximation is described as a way of feature extraction, data compaction, and noise filtering of boundaries of regions of pictures and waveforms. A new fast algorithm is proposed which allows for a variable number of segments. After an arbitrary initial choice, segments are split or merged in order to drive the error norm under a prespecified bound. Results of computer experiments with cell outlines and electrocardiograms are reported.
589 citations
TL;DR: The method has been integrated within a vision system coupled to an indutrial robot arm, to provide automatic picking and repositioning of partially overlapping industrial parts to provide strong robustness to partial occlusions.
Abstract: A new method has been designed to identify and locate objects lying on a flat surface. The merit of the approach is to provide strong robustness to partial occlusions (due for instance to uneven lighting conditions, shadows, highlights, touching and overlapping objects) thanks to a local and compact description of the objects boundaries and to a new fast recognition method involving generation and recursive evaluation of hypotheses named HYPER (HY potheses Predicted and Evaluated Recursively). The method has been integrated within a vision system coupled to an indutrial robot arm, to provide automatic picking and repositioning of partially overlapping industrial parts.
543 citations