Eye tracking on unmodified common tablets

Holland, Corey D.; Komogortsev, Oleg V.

doi:10.1145/2168556.2168615

Cited by 39 publications

(47 citation statements)

References 5 publications

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“…al. [11] (code is available under GPL3) and reached similar accuracies as mentioned in their paper. Yet, this method is not fit for our problem, as it requires a long training phase and is highly dependent on the user.…”

Section: Towards Robust Eyetrackingsupporting

confidence: 78%

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My reading life

Kunze

Ishimaru

Utsumi

et al. 2013

Proceedings of the 2013 ACM Conference on Pervasive and Ubiquitous Computing Adjunct Publication

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As reading is an integral part of our knowledge lives, we should know more about our reading activities. This paper introduces a reading application for smart phone and tablets that aims at giving user more quantified information about their reading habits. We present our work towards building an open library for eye tracking on unmodified tablets and smart phones to support some of the applications advanced functionality. We implemented already several eye tracking algorithms from previous work, unfortunately all seem not to be robust enough for our application case. We give an overview about our challenges and potential solutions.

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Section: Towards Robust Eyetrackingsupporting

confidence: 78%

“…using an appearance-based approach to estimate a user's gaze, training a neural network on different eye positions [11]. Also there are several papers that use commodity webcams for eye tracking [11]. Hansen et.…”

Section: Related Workmentioning

confidence: 99%

My reading life

Kunze

Ishimaru

Utsumi

et al. 2013

Proceedings of the 2013 ACM Conference on Pervasive and Ubiquitous Computing Adjunct Publication

View full text Add to dashboard Cite

show abstract

“…One problem that reduces eye tracking accuracy is the lack of consistent light [12]. In dim lit environments, cameras typically compensate poor illumination by increasing the exposure and gain.…”

Section: Stroboscopic Structured Lightingmentioning

confidence: 99%

A Fast and Accurate Eye Tracker Using Stroboscopic Differential Lighting

Borsato

Aluani

Morimoto

2015

2015 IEEE International Conference on Computer Vision Workshop (ICCVW)

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The use of video-based eye trackers (VETs) for gaze interaction have allowed people with severe motor disabilities to communicate more effectively. Nonetheless, current low cost VETs present limited accuracy and precision that impose several design constraints for gaze-based computer applications. In this paper we present an extension of the differential lighting (DL) technique for pupil detection and tracking using active light sources. The original technique was developed for analog interlaced cameras with external sync signal to synchronize the light sources with the video signal. In this paper we introduce the Stroboscopic DL technique that can be used with any rolling shutter camera, even those with no external sync. We have developed a computer vision technique to adjust the firing of the stroboscopic lights. Our new algorithm also exploits characteristics of pupil images to improve the accuracy of the tracking algorithm. Another advantage of the method is that using flashed pulses of light creates a virtual exposure time, reducing motion blur and temporal shear in the video volume. A real-time 187 fps prototype of the system was implemented using a low cost PS3 camera. Experimental results comparing the performance of our algorithm with Starburst show significant accuracy and speed improvement.

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“…While the mouse, keyboard, and other touch-based interfaces have long reigned as the primary input mediums associated with the field of human computer interaction, as advances continue to improve the cost and accuracy of eye tracking systems they stand poised to contend for this role [3]. An open and close eye template for blink pattern decisions based on correlation measurement is used in [4].…”

Section: Introductionmentioning

confidence: 99%

Efficient Eye Blink Detection Method for disabled-helping domain

Mohammed¹,

Anwer²

2014

IJACSA

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Abstract-In this paper, we present a real time method based on some video and image processing algorithms for eye blink detection. The motivation of this research is the need of disabling who cannot control the calls with human mobile interaction directly without the need of hands. A Haar Cascade Classifier is applied for face and eye detection for getting eye and facial axis information. In addition, the same classifier is used based on Haar-like features to find out the relationship between the eyes and the facial axis for positioning the eyes. An efficient eye tracking method is proposed which uses the position of detected face. Finally, an eye blinking detection based on eyelids state (close or open) is used for controlling android mobile phones. The method is used with and without smoothing filter to show the improvement of detection accuracy. The application is used in real time for studying the effect of light and distance between the eyes and the mobile device in order to evaluate the accuracy detection and overall accuracy of the system. Test results show that our proposed method provides a 98% overall accuracy and 100% detection accuracy for a distance of 35 cm and an artificial light.

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Eye tracking on unmodified common tablets

Cited by 39 publications

References 5 publications

My reading life

My reading life

A Fast and Accurate Eye Tracker Using Stroboscopic Differential Lighting

Efficient Eye Blink Detection Method for disabled-helping domain

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