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DEPTH FROM GAZE

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Citation Author(s):
Tzu-Sheng Kuo, Kuang-Tsu Shih, Sheng-Lung Chung, Homer Chen
Submitted by:
Tzu-Sheng Kuo
Last updated:
17 October 2018 - 6:44pm
Document Type:
Poster
Document Year:
2018
Event:
Presenters Name:
Tzu-Sheng Kuo
Paper Code:
2853

Abstract 

Abstract: 

Eye trackers are found on various electronic devices. In this paper, we propose to exploit the gaze information acquired by an eye tracker for depth estimation. The data collected from the eye tracker in a fixation interval are used to estimate the depth of a gazed object. The proposed method can be used to construct a sparse depth map of an augmented reality space. The resulting depth map can be applied to, for example, controlling the visual information displayed to the viewer. A mathematical model for determining whether two depths in the augmented reality space are statistically distinguishable is also developed. Experimental results show that the proposed method can estimate and distinguish different object depths effectively.

Please refer to our paper at https://ieeexplore.ieee.org/document/8451156 for more details.

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Poster.pdf

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