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Title: Object popping-out and characterization based on the human visual mechanism
Authors: Fu, H
Chi, Z 
Feng, D
Keywords: Human’s attention model
Object detection
Image representation
Issue Date: 2006
Source: International journal of information technology, 2006, v. 12, no. 5, p. 56-64 How to cite?
Journal: International journal of information technology 
Abstract: Semantic image understanding is the basis of a well-performed image management system on a large database whereas current image representations are neither powerful nor semantic-based. In this paper, the human vision mechanism from psychological studies is employed in order to understand an image at a higher level by constructing a layered representation structure based on the image segmentation result. An iterative object popping-out algorithm is proposed to locate the visually attentive objects from a downsized image by maximizing a global attention function designed according to the human’s attention model. The extracted objects are then characterized by using the original image while leaving the background as a rough description so as to construct a layered representation of the image. Promising results that agree with human’s intuition are obtained, showing the potential of our approach in image retrieval and other related aspects of image management.
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