Detecting structure by symbolic constructions on tokens
Computer Vision, Graphics, and Image Processing - Special issue on human and machine vission, part II
Computer Vision, Graphics, and Image Processing
A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Data- and Model-Driven Gaze Control for an Active-Vision System
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object-based visual attention for computer vision
Artificial Intelligence
Skeletal Shape Extraction from Dot Patterns by Self-Organization
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume IV-Volume 7472 - Volume 7472
Evaluation of Visual Attention Models for Robots
ICVS '06 Proceedings of the Fourth IEEE International Conference on Computer Vision Systems
A Coherent Computational Approach to Model Bottom-Up Visual Attention
IEEE Transactions on Pattern Analysis and Machine Intelligence
Implementation of visual attention system using bottom-up saliency map model
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
Selective tuning: feature binding through selective attention
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
A computational approach to illusory contour perception based on the tensor voting technique
CIARP'05 Proceedings of the 10th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis and Applications
Goal-directed search with a top-down modulated computational attention system
PR'05 Proceedings of the 27th DAGM conference on Pattern Recognition
Fast Saliency-Based Motion Segmentation Algorithm for an Active Vision System
ACIVS '08 Proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems
Color Saliency and Inhibition Using Static and Dynamic Scenes in Region Based Visual Attention
Attention in Cognitive Systems. Theories and Systems from an Interdisciplinary Viewpoint
Towards Standardization of Evaluation Metrics and Methods for Visual Attention Models
Attention in Cognitive Systems
Towards standardization of metrics for evaluation of artificial visual attention
Proceedings of the 10th Performance Metrics for Intelligent Systems Workshop
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A natural (human) eye can easily detect large visual patterns or objects emerging from spatially distributed discrete entities. This aspect of pattern analysis has been barely addressed in literature. We propose a biologically inspired approach derived from the concept of visual attention to associate together the distributed pieces of macro level patterns. In contrast to the usual approach practiced by the existing models of visual attention, this paper introduces a short-term excitation on the features and locations related to the current focus of attention in parallel to the spatial inhibition of return. This causes the attention system to fixate on analogous units in the scene that may formulate a meaningful global pattern. It is evident from the results of experiments that the outcome of this process can help in widening the scope of intelligent machine vision.