A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hierarchical Discriminant Regression
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object-based visual attention for computer vision
Artificial Intelligence
Incremental Hierarchical Discriminant Regression for Online Image Classification
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
A context-dependent attention system for a social robot
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Computer Vision and Image Understanding - Special issue: Attention and performance in computer vision
A model of dynamic visual attention for object tracking in natural image sequences
IWANN'03 Proceedings of the Artificial and natural neural networks 7th international conference on Computational methods in neural modeling - Volume 1
An attention selection system based on neural network and its application in tracking objects
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
A visual attention-based approach for automatic landmark selection and recognition
WAPCV'04 Proceedings of the Second international conference on Attention and Performance in Computational Vision
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This paper proposes a novel attention selection system with competition neural network supervised by visual memory. As compared with others, this system can not only attend some salient regions randomly according to sensory information but also mainly focus on some learned objects by the visual memory. So it can be applied in robot self-localization or object tracking. The weights of neural networks can be adapted in real time to environment change.