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基于模糊系统的近红外摄像头凝视追踪器目标选择

Fuzzy System-Based Target Selection for a NIR Camera-Based Gaze Tracker.

作者信息

Naqvi Rizwan Ali, Arsalan Muhammad, Park Kang Ryoung

机构信息

Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, Seoul 100-715, Korea.

出版信息

Sensors (Basel). 2017 Apr 14;17(4):862. doi: 10.3390/s17040862.

DOI:10.3390/s17040862
PMID:28420114
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5424739/
Abstract

Gaze-based interaction (GBI) techniques have been a popular subject of research in the last few decades. Among other applications, GBI can be used by persons with disabilities to perform everyday tasks, as a game interface, and can play a pivotal role in the human computer interface (HCI) field. While gaze tracking systems have shown high accuracy in GBI, detecting a user's gaze for target selection is a challenging problem that needs to be considered while using a gaze detection system. Past research has used the blinking of the eyes for this purpose as well as dwell time-based methods, but these techniques are either inconvenient for the user or requires a long time for target selection. Therefore, in this paper, we propose a method for fuzzy system-based target selection for near-infrared (NIR) camera-based gaze trackers. The results of experiments performed in addition to tests of the usability and on-screen keyboard use of the proposed method show that it is better than previous methods.

摘要

基于注视的交互（GBI）技术在过去几十年一直是热门的研究课题。在其他应用中，GBI可供残疾人用于执行日常任务、作为游戏界面，并且在人机交互（HCI）领域可以发挥关键作用。虽然注视跟踪系统在GBI中已显示出高精度，但在使用注视检测系统时，检测用户用于目标选择的注视是一个需要考虑的具有挑战性的问题。过去的研究为此使用了眼睛眨眼以及基于停留时间的方法，但这些技术要么对用户不方便，要么目标选择需要很长时间。因此，在本文中，我们提出了一种基于模糊系统的目标选择方法，用于基于近红外（NIR）相机的注视跟踪器。除了对所提出方法的可用性和屏幕键盘使用进行测试之外，所进行的实验结果表明它比以前的方法更好。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37e7/5424739/4038da4aed74/sensors-17-00862-g020.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37e7/5424739/564a1a6fca7a/sensors-17-00862-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37e7/5424739/2bbf55ff3c80/sensors-17-00862-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37e7/5424739/19e360c7318a/sensors-17-00862-g011.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37e7/5424739/12b824e3b29e/sensors-17-00862-g019.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37e7/5424739/4038da4aed74/sensors-17-00862-g020.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37e7/5424739/45491b659b3f/sensors-17-00862-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37e7/5424739/3d3e72b4727e/sensors-17-00862-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37e7/5424739/96f4f38b25b6/sensors-17-00862-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37e7/5424739/03dbd8c8f28a/sensors-17-00862-g004.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37e7/5424739/058c48c2bd10/sensors-17-00862-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37e7/5424739/d09cef573798/sensors-17-00862-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37e7/5424739/564a1a6fca7a/sensors-17-00862-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37e7/5424739/2bbf55ff3c80/sensors-17-00862-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37e7/5424739/19e360c7318a/sensors-17-00862-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37e7/5424739/26a33c76f59e/sensors-17-00862-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37e7/5424739/11fdb8d486e5/sensors-17-00862-g013a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37e7/5424739/d4b29cdbc6cc/sensors-17-00862-g014a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37e7/5424739/fac9c8a2ffe2/sensors-17-00862-g015a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37e7/5424739/029bf9b70c81/sensors-17-00862-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37e7/5424739/0607b6809d20/sensors-17-00862-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37e7/5424739/90a24be31a24/sensors-17-00862-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37e7/5424739/12b824e3b29e/sensors-17-00862-g019.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37e7/5424739/4038da4aed74/sensors-17-00862-g020.jpg

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