Implementation of visual attention system using bottom-up saliency map model

Authors:
Sang-Jae Park;Sang-Woo Ban;Jang-Kyoo Shin;Minho Lee
Affiliations:
Dept. of Sensor Engineering, Kyungpook National University, Taegu, Korea;School of Electronic and Electrical Engineering, Kyungpook National University, Taegu, Korea;School of Electronic and Electrical Engineering, Kyungpook National University, Taegu, Korea;School of Electronic and Electrical Engineering, Kyungpook National University, Taegu, Korea
Venue:
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
Year:
2003

Citing 7
Cited 3

A Model of Saliency-Based Visual Attention for Rapid Scene Analysis

IEEE Transactions on Pattern Analysis and Machine Intelligence
Biologically Inspired Saliency Map Model for Bottom-up Visual Attention

BMCV '02 Proceedings of the Second International Workshop on Biologically Motivated Computer Vision
A Goal Oriented Attention Guidance Model

BMCV '02 Proceedings of the Second International Workshop on Biologically Motivated Computer Vision
Hierarchical Selectivity for Object-Based Visual Attention

BMCV '02 Proceedings of the Second International Workshop on Biologically Motivated Computer Vision
Attentional Selection for Object Recognition A Gentle Way

BMCV '02 Proceedings of the Second International Workshop on Biologically Motivated Computer Vision
Stochastic Guided Search Model for Search Asymmetries in Visual Search Tasks

BMCV '02 Proceedings of the Second International Workshop on Biologically Motivated Computer Vision
Visual Attention Using Game Theory

BMCV '02 Proceedings of the Second International Workshop on Biologically Motivated Computer Vision

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
An adaptive detection/attention mechanism for real time robot operation

Neurocomputing
An attentional approach for perceptual grouping of spatially distributed patterns

Proceedings of the 29th DAGM conference on Pattern recognition

Quantified Score

Hi-index	0.00

Visualization

Abstract

We propose a new active vision system that mimics humanlike bottom-up visual attention using saliency map model based on independent component analysis. We consider the feature bases reflecting the biological features and psychological effect to construct the saliency map model, and the independent component analysis is used for integration of the feature bases to implement human-like visual attention system. Using the CCD camera, a DSP board, and DC motors with PID controllers, we implement an active vision system that can automatically select a visual attention area.