A new objective visual fatigue measurement system by using a remote infrared camera

Kim, Jin Man; Lee, Eui Chul; Lim, Jao Sang

doi:10.1109/jcsse.2011.5930117

Cited by 5 publications

(2 citation statements)

References 17 publications

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“…Until now, eye-tracking applications have mainly concentrated on behavior analysis and HCI [9]. In terms of behavior analysis, by analyzing human gaze time and changes in gaze angle, we can analyze hand-eye coordination [10], students' attention in class [11], visual fatigue [12], and even emotional state [13]. In addition, eye tracking plays an auxiliary role in the diagnosis of diseases such as autism [14], visual memory impairment [15], and mild amnestic cognitive impairment [16].…”

Section: Introductionmentioning

confidence: 99%

Gaze Gestures and Their Applications in human-computer interaction with a head-mounted display

Chen¹,

Cui²,

Zheng³

et al. 2019

Preprint

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A head-mounted display (HMD) is a portable and interactive display device. With the development of 5G technology, it may become a general-purpose computing platform in the future. Human-computer interaction (HCI) technology for HMDs has also been of significant interest in recent years. In addition to tracking gestures and speech, tracking human eyes as a means of interaction is highly effective. In this paper, we propose two UnityEyes-based convolutional neural network models, UEGazeNet and UEGazeNet*, which can be used for input images with low resolution and high resolution, respectively. These models can perform rapid interactions by classifying gaze trajectories (GTs), and a GTgestures dataset containing data for 10,200 "eye-painting gestures" collected from 15 individuals is established with our gaze-tracking method. We evaluated the performance both indoors and outdoors and the UEGazeNet can obtaine results 52% and 67% better than those of state-of-the-art networks. The generalizability of our GTgestures dataset using a variety of gaze-tracking models is evaluated, and an average recognition rate of 96.71% is obtained by our method.

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Section: Introductionmentioning

confidence: 99%

Gaze Gestures and Their Applications in human-computer interaction with a head-mounted display

Chen¹,

Cui²,

Zheng³

et al. 2019

Preprint

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show abstract

“…Non wearable face capture camera and an example of captured image(Kim et al, 2011). (a) Remote camera device (5 mega pixel, IEEE 1394b interface).…”

mentioning

confidence: 99%

Classification between Intentional and Natural Blinks in Infrared Vision Based Eye Tracking System

Kim¹,

Noh²,

Kim³

et al. 2012

Journal of the Ergonomics Society of Korea

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Objective: The aim of this study is to classify between intentional and natural blinks in vision based eye tracking system. Through implementing the classification method, we expect that the great eye tracking method will be designed which will perform well both navigation and selection interactions. Background: Currently, eye tracking is widely used in order to increase immersion and interest of user by supporting natural user interface. Even though conventional eye tracking system is well focused on navigation interaction by tracking pupil movement, there is no breakthrough selection interaction method. Method: To determine classification threshold between intentional and natural blinks, we performed experiment by capturing eye images including intentional and natural blinks from 12 subjects. By analyzing successive eye images, two features such as eye closed duration and pupil size variation after eye open were collected. Then, the classification threshold was determined by performing SVM(Support Vector Machine) training. Results: Experimental results showed that the average detection accuracy of intentional blinks was 97.4% in wearable eye tracking system environments. Also, the detecting accuracy in non-wearable camera environment was 92.9% on the basis of the above used SVM classifier. Conclusion: By combining two features using SVM, we could implement the accurate selection interaction method in vision based eye tracking system. Application: The results of this research might help to improve efficiency and usability of vision based eye tracking method by supporting reliable selection interaction scheme.

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EmoSens – The Proposal of System for Recognition of Emotion with SDK Affectiva and Various Sensors

Magdin

Kohutek

Koprda

et al. 2019

Intelligent Computing Theories and Application

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A new objective visual fatigue measurement system by using a remote infrared camera

Cited by 5 publications

References 17 publications

Gaze Gestures and Their Applications in human-computer interaction with a head-mounted display

Gaze Gestures and Their Applications in human-computer interaction with a head-mounted display

Classification between Intentional and Natural Blinks in Infrared Vision Based Eye Tracking System

EmoSens – The Proposal of System for Recognition of Emotion with SDK Affectiva and Various Sensors

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