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Journal Article Multi-Modal User Interaction Method Based on Gaze Tracking and Gesture Recognition
Cited 15 time in scopus Share share facebook twitter linkedin kakaostory
Authors
Heekyung Lee, Seong Yong Lim, Injae Lee, Jihun Cha, Dong-Chan Cho, Sunyoung Cho
Issue Date
2013-02
Citation
Signal Processing : Image Communication, v.28, no.2, pp.114-126
ISSN
0923-5965
Publisher
Elsevier
Language
English
Type
Journal Article
DOI
https://dx.doi.org/10.1016/j.image.2012.10.007
Abstract
This paper presents a gaze tracking technology which provides a convenient human-centric interface for multimedia consumption without any wearable device. It enables a user to interact with various multimedia on a large display in distance by tracking user movement and acquiring high resolution eye images. This paper also presents a gesture recognition technology which is helpful to interact with scene descriptions in terms of controlling and rendering scene objects. It is based on Hidden Markov Model and CRF using a commercial depth sensor. And then, this paper shows a collaboration method with those new sensors and MPEG standards in order to achieve interoperability among interactive applications, new user interaction devices and users. © 2012 Elsevier B.V. All rights reserved.
KSP Keywords
Depth sensor, High-resolution, Interaction devices, Multi-modal User Interaction, Tracking technology, Wearable device, gaze tracking, gesture recognition technology, hidden Markov Model, human-centric, interactive applications