DocumentCode
351128
Title
Neural model of visual selective attention for automatic translation invariant object recognition in cluttered images
Author
Chong, Eric W. ; Lim, Cheng-Chew ; Lozo, Peter
Author_Institution
Dept. of Electr. & Electron. Eng., Adelaide Univ., SA, Australia
fYear
1999
fDate
36495
Firstpage
373
Lastpage
376
Abstract
This paper presents a biologically inspired neural model for detecting, locating and recognising all known objects in the visual scene automatically. In particular, this model employs bottom-up segmentation to achieve shifts in spatial attention, for selecting potential regions of interest across the visual scene
Keywords
computer vision; image segmentation; invariance; neural net architecture; noise; object detection; object recognition; automatic translation-invariant object recognition; biologically inspired neural model; bottom-up image segmentation; cluttered images; object detection; object location; object recognition; potential region-of-interest selection; spatial attention shifts; visual scene; visual selective attention; Australia; Biological system modeling; Brain modeling; Humans; Image segmentation; Layout; Neural networks; Object detection; Object recognition; Visual perception;
fLanguage
English
Publisher
ieee
Conference_Titel
Knowledge-Based Intelligent Information Engineering Systems, 1999. Third International Conference
Conference_Location
Adelaide, SA
Print_ISBN
0-7803-5578-4
Type
conf
DOI
10.1109/KES.1999.820201
Filename
820201
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