DocumentCode
2340404
Title
Computational model of selective attention for machine vision based on adapted entropy
Author
Tian, Yan-tao ; Lian, Tao ; Yu, Da-Chuan ; Xiao, Jie-Wei
Author_Institution
Coll. of Commun. & Eng., Jilin Univ., Changchun, China
Volume
9
fYear
2005
fDate
18-21 Aug. 2005
Firstpage
5388
Abstract
The selective attention for machine vision can reduce the complexity of calculation. This paper adapted entropy as a measurement to the salience of interested object region and proposed a new computational model of attention selection. Analysis proved that this method simulated the selective attention of human being effectively and was easy for engineering realization. Experiments showed the feasibility and efficiency of the calculation model.
Keywords
computer vision; entropy; object recognition; adapted entropy; computational model; machine vision; object region; salience map; selective attention; Analytical models; Computational modeling; Computer vision; Educational institutions; Entropy; Humans; Image processing; Layout; Machine vision; Pixel; Entropy; Machine vision; Salience map; Selective attention;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location
Guangzhou, China
Print_ISBN
0-7803-9091-1
Type
conf
DOI
10.1109/ICMLC.2005.1527896
Filename
1527896
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