Salient Region Detection Using Weighted Feature Maps Based on the Human Visual Attention Model

2004 ◽  
pp. 993-1000 ◽  
Author(s):  
Yiqun Hu ◽  
Xing Xie ◽  
Wei-Ying Ma ◽  
Liang-Tien Chia ◽  
Deepu Rajan
Keyword(s):  
Visual Attention ◽  
Feature Maps ◽  
Salient Region Detection ◽  
Visual Attention Model ◽  
Attention Model ◽  
Salient Region ◽  
Region Detection ◽  
Human Visual Attention

A VISUAL ATTENTION MODEL FOR NATURAL SCENES BASED ON DYNAMIC FEATURE COMBINATION

2010 ◽  
Vol 20 (08) ◽  
pp. 1077-1095
Author(s):  
MINGHUI TIAN ◽  
SHOUHONG WAN ◽  
LIHUA YUE
Keyword(s):  
Visual Attention ◽  
Natural Scenes ◽  
Dynamic Feature ◽  
Feature Combination ◽  
Feature Maps ◽  
Combination Strategy ◽  
Visual Attention Model ◽  
The Real ◽  
Attention Model ◽  
Human Visual Attention

In recent years, many research works indicate that human's visual attention is very helpful in some research areas that are related to computer vision, such as object recognition, scene understanding and object-based image/video retrieval or annotation. This paper presents a visual attention model for natural scenes based on a dynamic feature combination strategy. The model can be divided into three parts, which are feature extraction, dynamic feature combination and salient objects detection. First, the saliency features of color, information entropy and salient boundary are extracted from an original colored image. After that, two different evaluation measurements are proposed for two different categories of feature maps defined in this dynamic combination strategy, which measures the contribution of each feature map to saliency and carries out a dynamic weighting of individual feature maps. Finally, salient objects are located from an integrated saliency map and a computational method is given to simulate the location shift of the real human visual attention. Experimental results show that this model is effective and robust for saliency detection in natural scenes, also similar to the real human visual attention mechanism.

Visual Attention Distribution and its Application in the Gesture Interaction System

2015 ◽  
Vol 713-715 ◽  
pp. 2185-2188
Author(s):  
Na Na He ◽  
Zhi Quan Feng ◽  
Zhong Zhu Huang ◽  
Xue Wen Yang
Keyword(s):  
Visual Attention ◽  
Cognitive Model ◽  
Distribution Model ◽  
Tracking Accuracy ◽  
Gesture Interaction ◽  
Visual Attention Model ◽  
Attention Model ◽  
Gesture Tracking ◽  
Basic Characteristics ◽  
Human Visual Attention

Aiming at making the simulation of human visual attention behavior more truly in computer, starting from analyzing operator’s cognitive model, a gesture tracking algorithm is put forward based on the distribution model of visual attention. To begin with, analyzing the change of the operator human eye sight, a visual attention model was built. Secondly, the basic characteristics of visual attention model were studied. Finally, the three Gauss formula is used to describe the model. Experimental results show that the algorithm can effectively improve the speed and tracking accuracy of gesture interaction.

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