Visual Attention Distribution and its Application in the Gesture Interaction System

Na Na He; Zhi Quan Feng; Zhong Zhu Huang; Xue Wen Yang

doi:10.4028/www.scientific.net/AMM.713-715.2185

Paper Titles

Application of SOM Neural Network in Lithology Recognition
p.2169

2D Bar Code Detection, Recognition and Application Research Based on NI VISION
p.2173

Improvement and Kernelization of T-2DPCA with Application to Face Recognition
p.2177

The Poultry Meat Production Technical Efficiency Analysis Model Based on Intelligent Devices
p.2181

Visual Attention Distribution and its Application in the Gesture Interaction System
p.2185

Research on Computer Graphics Design and Visual Communication Design
p.2191

A Discovery Technology Based on Distributed Resource Management Domain
p.2195

A Multipath Routing Protocol Based on the Quality of Service Aware
p.2199

A New Web Application Framework Based on SSH
p.2203

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 713-715Visual Attention Distribution and its Application...

Visual Attention Distribution and its Application in the Gesture Interaction System

Abstract:

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.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 713-715)

Pages:

2185-2188

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.713-715.2185

Citation:

Cite this paper

Online since:

January 2015

Authors:

Na Na He*, Zhi Quan Feng, Zhong Zhu Huang, Xue Wen Yang

Keywords:

Gauss Formula, Gesture Interaction, Visual Attention

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] A. Borji, L. Itti, State-of-the-art in Visual Attention Modeling, IEEE Transactions on Analysis and Machine Intelligence, vol. 35, pp.185-207, (2013).

DOI: 10.1109/tpami.2012.89

Google Scholar

[2] Laurent I, Carl G, Christ K. Visual Attention and Target Detection in Cluttered Natural Scenes[J]. Optical Engineering, 2001, 40(9): 1784-1793.

DOI: 10.1117/1.1389063

Google Scholar

[3] Zhao Xin-Can, Zuo Hong-Fu., Ren Yong-Jun. A review of eye tracker and eye tracking techniques. Computer Engineering and Applications, 2006, 42(12), pp.118-120 , 2006.

Google Scholar

[4] Feng Zhi-quan, Yang Bo, Zheng Yan-wei, Tang Hao-Kui, Li Yi. Initialization of 3D Human Hand Model and Its Applications in Human Hand Tracking. Journal of Computers, 7(2), pp.419-426, (2012).

DOI: 10.4304/jcp.7.2.419-426

Google Scholar

[5] Morshidi, M., & Tjahjadi, T. Gravity optimised particle filter for hand tracking. Pattern Recognition, 47(1), pp.194-207, (2013).

DOI: 10.1016/j.patcog.2013.06.032

Google Scholar

[6] Feng Zhi-quan, Yang Bo, Li Yi, et al. Real-time oriented behavior-driven 3D freehand tracking for direct interaction. Pattern Recognition, 46(2), pp.590-608, (2013).

DOI: 10.1016/j.patcog.2012.07.019

Google Scholar

[7] Lin Yan, Feng Zhi-Quan, Zhu De-Liang et. Three-dimensional hand tracking algorithm characterized by multimodal fusion. Journal of Computer-Aided Design & Computer Graphics, 25(4), pp.450-459 , 2013.

Google Scholar