Real-time non-intrusive eye tracking for human-computer interaction

Wu, Tunhua; Bai, Baogang; Zhou, Changle; Li, Shaozi; Lin, Kwei-Jay

doi:10.1109/iccse.2010.5593420

Cited by 4 publications

(3 citation statements)

References 7 publications

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“…W. Tunhua, B. Baogang , Z. Changle, L. Shaozi and L. Kunhui [9] proposed a system of a real-time eye tracking that uses differents algorithms such us Adaboost, optical flow and Camshaft. This algorithm is based on 4 steps: First, it standardized the light condition and the camera was placed in front of user.…”

Section: B Eye Trackingmentioning

confidence: 99%

Smart Tablet Monitoring by a Real-Time Head Movement and Eye Gestures Recognition System

Elleuch¹,

Wali²,

Alimi³

2015

IJCDS

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Different research works are studying to integrate new ways of interaction with mobiles devices such as smartphone and tablets to provide a natural and easy mode of communication to people. In this paper we proposed a new system to monitoring tablets through head motions and eye-gaze gestures recognition. This system is able to open browser application with simples motions by the head and the eyes. For the face detection we used a viola and jones technique, and for the eyes detection and tracking we used Haar classifier to the detection part and the template matching for tracking. We develop this system on android based tablet. Through the front-facing camera the system capture a real-time streaming video on which we implemented the detection and recognition module. We tested the system on 10 persons and the experiment results shows that this system is robust and it is invariant for the lightness and the moving state of the user. We introduce also in this system, a module to estimate point of regard on the tablet's screen based only on the front-facing camera. As known the tablets resources are limited, in consequence the response time of our system is not satisfied for the real time condition. That is why we apply the cloud computing to solve this problem.

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Section: B Eye Trackingmentioning

confidence: 99%

Smart Tablet Monitoring by a Real-Time Head Movement and Eye Gestures Recognition System

Elleuch¹,

Wali²,

Alimi³

2015

IJCDS

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“…Eye movement is the most common and obvious pattern of visual behavior, so it attracts more and more researchers' attention to its practical applications, such as humancomputer interface (HCI) [1], driver fatigue detection [3], health care [2], military, cognitive science [4] and so on. A lot of computer manufacturers and software developers endeavor to enhance their products by adding more and more natural interfaces, such as Swedish firm Tobii, which specializes in eye control, teamed up with Lenovo, the world's fourth largest manufacturer of personal computers, to show the world's first eye-controlled laptops at CeBIT 2011 in Hannover, Germany [8].…”

Section: Introductionmentioning

confidence: 99%

“…Non-intrusive methods often use normal cameras and PC as instruments and deal with the facial images to extract the eyes. At present, the methods for eye detection mainly utilize edge detection, morphological operations, or template matching [1], while algorithms like the Mean-Shift [9], Camshift [1], optical flow [1] [11]and Kalman filter [9] [12] are often applied to eye tracking.…”

Section: Introductionmentioning

confidence: 99%

The real-time eye-controlled system based on the near-field video streams

Chen

Han

Lan

et al. 2011

2011 IEEE International Symposium on IT in Medicine and Education

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Eye movement is a direct expression of human's visual intent. The paper presents a novel system which is focusing on utilizing eye movement information as control source and the video streams from a remote pan-tilt-zoom (PTZ) camera as feedback. By processing left and right eye images simultaneously, the system can recognize the direction of eye movement and adjust the motion of remote PTZ camera to synchronize with the eye movement. Meanwhile, the user who is wearing video glasses (head-mounted display) can see the images captured by the PTZ camera. Besides, a robust algorithm is also put forward to overcome the interferences caused by the instability of background brightness and ways of wearing video glasses.

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