Gaze estimation based on head movements in virtual reality applications using deep learning | IEEE Conference Publication | IEEE Xplore

Gaze estimation based on head movements in virtual reality applications using deep learning


Abstract:

Gaze detection in Virtual Reality systems is mostly performed using eye-tracking devices. The coordinates of the sight, as well as other data regarding the eyes, are used...Show More

Abstract:

Gaze detection in Virtual Reality systems is mostly performed using eye-tracking devices. The coordinates of the sight, as well as other data regarding the eyes, are used as input values for the applications. While this trend is becoming more and more popular in the interaction design of immersive systems, most visors do not come with an embedded eye-tracker, especially those that are low cost and maybe based on mobile phones. We suggest implementing an innovative gaze estimation system into virtual environments as a source of information regarding users intentions. We propose a solution based on a combination of the features of the images and the movement of the head as an input of a Deep Convolutional Neural Network capable of inferring the 2D gaze coordinates in the imaging plane.
Date of Conference: 18-22 March 2017
Date Added to IEEE Xplore: 06 April 2017
ISBN Information:
Electronic ISSN: 2375-5334
Conference Location: Los Angeles, CA, USA

References

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