Deep belief network based gaze tracker for auto-aiming system

Chih Wei Chien, Ting Nan Tsai, L. F. Wu, N. C. Fang, C. Y. Liu, Tzuu Hseng S. Li

研究成果: Conference contribution

摘要

This paper proposes a design of an auto-aiming system, which is capable of tracking a user's gaze automatically. The auto-aiming system is composed of an electric gun control system and a wearable gaze tracker. According to a user's gaze direction which is captured by the helmet camera, the gun can automatically aim an object which the user is looking at. The mapping model between the user's eye movement and the shooting direction of the gun is established by a Deep Belief Network (DBN). This DBN-based gaze tracking model allows the auto-aiming shooting system to aim the target timely and accurately. Finally, the experiment results demonstrate the proposed auto-aiming system for different users can achieve an average accuracy of 96%.

原文English
主出版物標題2017 International Conference on Advanced Robotics and Intelligent Systems, ARIS 2017
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(列印)9781538624197
DOIs
出版狀態Published - 2018 二月 20
事件2017 International Conference on Advanced Robotics and Intelligent Systems, ARIS 2017 - Taipei, Taiwan
持續時間: 2017 九月 62017 九月 8

出版系列

名字International Conference on Advanced Robotics and Intelligent Systems, ARIS
2017-September
ISSN(列印)2374-3255
ISSN(電子)2572-6919

Other

Other2017 International Conference on Advanced Robotics and Intelligent Systems, ARIS 2017
國家Taiwan
城市Taipei
期間17-09-0617-09-08

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Artificial Intelligence

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  • 引用此

    Chien, C. W., Tsai, T. N., Wu, L. F., Fang, N. C., Liu, C. Y., & Li, T. H. S. (2018). Deep belief network based gaze tracker for auto-aiming system. 於 2017 International Conference on Advanced Robotics and Intelligent Systems, ARIS 2017 [8297183] (International Conference on Advanced Robotics and Intelligent Systems, ARIS; 卷 2017-September). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ARIS.2017.8297183