A neural matching algorithm for 3-D reconstruction from stereo pairs of linear images
In this paper, we propose a neural approach for obstacle detection in front of moving cars, using linear stereo vision. The key problem is the so-called “correspondence problem” which consists in matching features extracted from two images that are projections of the same entity in the three-dimensi...
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          | Published in | Pattern recognition letters Vol. 17; no. 4; pp. 387 - 398 | 
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| Main Authors | , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
            Elsevier B.V
    
        04.04.1996
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| Subjects | |
| Online Access | Get full text | 
| ISSN | 0167-8655 1872-7344  | 
| DOI | 10.1016/0167-8655(95)00134-4 | 
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| Abstract | In this paper, we propose a neural approach for obstacle detection in front of moving cars, using linear stereo vision. The key problem is the so-called “correspondence problem” which consists in matching features extracted from two images that are projections of the same entity in the three-dimensional world. The linear stereo correspondence problem is first formulated as an optimization task where an energy function, which represents the constraints on the solution, is to be minimized. The optimization problem is then performed by means of a Hopfield neural network. Experimental results, using real stereo images, demonstrate the effectiveness of the method. | 
    
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| AbstractList | In this paper, we propose a neural approach for obstacle detection in front of moving cars, using linear stereo vision. The key problem is the so-called “correspondence problem” which consists in matching features extracted from two images that are projections of the same entity in the three-dimensional world. The linear stereo correspondence problem is first formulated as an optimization task where an energy function, which represents the constraints on the solution, is to be minimized. The optimization problem is then performed by means of a Hopfield neural network. Experimental results, using real stereo images, demonstrate the effectiveness of the method. | 
    
| Author | Postaire, J.-G. Ruichek, Y.  | 
    
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| Keywords | Matching Real-time processing Obstacle detection Neural network Linear stereo vision Optimization  | 
    
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| SubjectTerms | Linear stereo vision Matching Neural network Obstacle detection Optimization Real-time processing  | 
    
| Title | A neural matching algorithm for 3-D reconstruction from stereo pairs of linear images | 
    
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