BOOK-CHAPTER

Computational Models of Visual Attention

Rajarshi Pal

Year: 2013 Advances in computational intelligence and robotics book series Pages: 54-76   Publisher: IGI Global

Abstract

Even the enormous processing capacity of the human brain is not enough to handle all the visual sensory information that falls upon the retina. Still human beings can efficiently respond to the external stimuli. Selective attention plays an important role here. It helps to select only the pertinent portions of the scene being viewed for further processing at the deeper brain. Computational modeling of this neuro-psychological phenomenon has the potential to enrich many computer vision tasks. Enormous amounts of research involving psychovisual experiments and computational models of attention have been and are being carried out all within the past few decades. This article compiles a good volume of these research efforts. It also discusses various aspects related to computational modeling of attention–such as, choice of features, evaluation of these models, and so forth.

Keywords:
Computational model Computer science Visual attention Cognitive science Artificial intelligence Human–computer interaction Cognition Neuroscience Psychology

Metrics

10
Cited By
2.88
FWCI (Field Weighted Citation Impact)
139
Refs
0.91
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Visual Attention and Saliency Detection
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Visual perception and processing mechanisms
Life Sciences →  Neuroscience →  Cognitive Neuroscience
Gaze Tracking and Assistive Technology
Physical Sciences →  Computer Science →  Human-Computer Interaction

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