DocumentCode :
1559071
Title :
Data- and model-driven gaze control for an active-vision system
Author :
Backer, Gerriet ; Mertsching, Bärbel ; Bollmann, Maik
Author_Institution :
Dept. of Comput. Sci., Hamburg Univ., Germany
Volume :
23
Issue :
12
fYear :
2001
fDate :
12/1/2001 12:00:00 AM
Firstpage :
1415
Lastpage :
1429
Abstract :
Models of visual attention provide a general approach to control the activities of active vision systems. We introduce a new model of attentional control that differs in important aspects from conventional ones. We divide the selection into two stages, which is more suitable for the system as well as explaining different phenomena found in natural visual attention, such as the dispute between early and late selection. The proposed model is especially designed for use in dynamic scenes. Our approach aims at modeling as much of a general active vision system as possible and designing clean interfaces for the integration of the remaining specific aspects needed in order to solve specific problems
Keywords :
active vision; feature extraction; image colour analysis; image sequences; object recognition; optical tracking; spatial variables control; active vision; color space; dynamic scenes; feature extraction; gaze control; image sequences; object recognition; tracking; visual attentional control; visual exploration; Biological system modeling; Computer vision; Concrete; Control system synthesis; Control systems; Humans; Layout; Machine vision; Psychology; Robustness;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/34.977565
Filename :
977565
Link To Document :
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