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Proceedings Paper

Eye gazing direction inspection based on image processing technique
Author(s): Qun Hao; Yong Song
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Paper Abstract

According to the research result in neural biology, human eyes can obtain high resolution only at the center of view of field. In the research of Virtual Reality helmet, we design to detect the gazing direction of human eyes in real time and feed it back to the control system to improve the resolution of the graph at the center of field of view. In the case of current display instruments, this method can both give attention to the view field of virtual scene and resolution, and improve the immersion of virtual system greatly. Therefore, detecting the gazing direction of human eyes rapidly and exactly is the basis of realizing the design scheme of this novel VR helmet. In this paper, the conventional method of gazing direction detection that based on Purklinje spot is introduced firstly. In order to overcome the disadvantage of the method based on Purklinje spot, this paper proposed a method based on image processing to realize the detection and determination of the gazing direction. The locations of pupils and shapes of eye sockets change with the gazing directions. With the aid of these changes, analyzing the images of eyes captured by the cameras, gazing direction of human eyes can be determined finally. In this paper, experiments have been done to validate the efficiency of this method by analyzing the images. The algorithm can carry out the detection of gazing direction base on normal eye image directly, and it eliminates the need of special hardware. Experiment results show that the method is easy to implement and have high precision.

Paper Details

Date Published: 10 February 2005
PDF: 9 pages
Proc. SPIE 5638, Optical Design and Testing II, (10 February 2005); doi: 10.1117/12.570341
Show Author Affiliations
Qun Hao, Beijing Institute of Technology (China)
Yong Song, Beijing Institute of Technology (China)


Published in SPIE Proceedings Vol. 5638:
Optical Design and Testing II
Yongtian Wang; Zhicheng Weng; Shenghua Ye; Jose M. Sasian, Editor(s)

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