Identification of Visual Attention Regions in Machine Vision using Saliency Map

In Recent years, the detection of visual attention regions (VAR) is becoming more noteworthy due to its valuable applications in the area of multimedia. In this paper, we provide the Saliency Map hypothesis and test results for identification of Visual Attention Regions in Machine Vision using Compu...

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Bibliographic Details
Main Authors: Kounte, Manjunath R., Sujatha, B. K.
Format: Conference Proceeding
Language:English
Subjects:
Computational Cognitive Neuroscience
Computational modeling
Genetics
Image segmentation
Lead
Neurophysiology
Saliency Map
Taxonomy
Visual Attention
Visual Attention Region
Visualization
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Summary:In Recent years, the detection of visual attention regions (VAR) is becoming more noteworthy due to its valuable applications in the area of multimedia. In this paper, we provide the Saliency Map hypothesis and test results for identification of Visual Attention Regions in Machine Vision using Computational Cognitive Neuroscience. We also review how Computational Cognitive Neuroscience approach is the best approach in order for the implementation of Saliency Map technique for identification of Visual Attention Regions (VAR) in Machine Vision in real time scenarios where the systems are evolved for exhibiting intelligence in real time scenarios. And also, we focus on learning how visual attention is beneficial to the machine vision community and explain why attention is considered a selective process by highlighting how in the last 25 years research on attention has characterized into multiple ways.
DOI:10.1109/ICCSP.2015.7322566