Dissertation > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device

Research on Visual Attention Model with Joint Spatial and Feature Domain Information

Author WuChunPeng
Tutor DuanLiJuan
School Beijing University of Technology
Course Computer Science and Technology
Keywords Visual attention Dissimilarity Spatial distance Central preferences Image scaling
CLC TP391.41
Type Master's thesis
Year 2011
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Note that the selection mechanism is an important characteristic of human visual perception , if the mechanism of the human visual system is introduced to computer vision system is bound to enhance the performance and efficiency of existing computer image analysis . Way to build their applications in order to explore the computational model of the human visual attention mechanisms , specific research work as follows : First, the paper reviews the bottom-up model of visual attention , since the top-down visual attention model and viewpoint transfer mechanism Research also describes the visual attention model in image segmentation, image classification and target detection . In-depth study of human attention mechanism , this paper analyzes the analog visual attention of three key factors : the spatial distance between the image dissimilarity between the local area , the image local area , local image regions to the center of the image distance central preference characteristics . Secondly, a joint airspace and the feature domain information visual attention model , the model on the basis of the three key factors , core step is the spatial distance between the image local area and central preference characteristics of the local area dissimilarity between modulation , and its essence is the image of each region of the human eye is defined as the degree of concern based on the spatial distance weighted global features response rarity . Multiple image libraries and video clips on different testing standards , test results show that compared with some well-known international attention model , more consistent with the viewpoint of the model predictions with real human viewpoint . Finally, the model is applied to content-based image scaling. The subject of the image is generally reflected in the character, nature, landscape , urban landscape semantic information , the lack of detection of this type of information the model , this paper on the basis of the model add a face , pedestrian and vehicle detector . The test results show that compared with the conventional image scaling method of the model - based approach , the foreground object in the image distortions can guarantee smaller .

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