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A Computational Model Of Visual Selective Attention Mechanism And Its Application In Object Recognition

Posted on:2006-02-03Degree:MasterType:Thesis
Country:ChinaCandidate:T F WuFull Text:PDF
GTID:2168360152490258Subject:Signal and Information Processing
Abstract/Summary:PDF Full Text Request
At the present, active vision is the hot field and the developmental direction of machine vision, in which the key problem is how to acquire visual information actively, intelligently and selectively under a given visual task. From the viewpoint of computation, it is to implement a computational model of visual selective attention mechanism to compute the saliency of image data.This thesis focused on the computational model of visual selective attention mechanism, including the following research contents:Firstly, a unified computational model of scale, saliency and object recognition is studied. In traditional studies of machine vision, the study on scale, saliency and object recognition are performed respectively. Contrary to the traditional idea, they are unified in this thesis in which the problem of scale in vision and the scale-space representation, the essence of the computation of saliency and the method of recognition based on local invariant feature are discussed.Secondly, a computational model of visual attention deployed by scale and features is studied. The model presented in the thesis aimed at the bottom-up aspect of covert attention which deployed by scale and features. Based on the research of neuroscience of visual attention, Intensity, color and orientation are used as the features attracted attention in this thesis. At first, a filter which has dual characteristics of competition and cooperation is created based on the mechanism of the visual receptive field and the integrated field, and the three primary feature maps are iterated by the filter to compute the feature-space saliency. Then the primary scale of the input image is estimated followed by the scale-space representation of the input image being generated. So far, the saliency of scale and features can be computed, and at the same time the optimal scale of the fixation is selected.Finally, a model which unified the visual attention and visual recognition is studied. Focusing on the problem of recognition in complex background, the thesis discussed how to combine the visual attention model presented in the thesis and the model of recognition based on local invariant features. The implementation of the unified model made it possible to reuse the features extracted in the stage of visualattention in the stage of recognition, and could add the background invariance into the traditional local invariant feature-based method.
Keywords/Search Tags:Active vision, Visual selective attention mechanism, Scale, Saliency, Local invariant feature-based recognition
PDF Full Text Request
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