Closed-Eye Gaze Gestures: Detection and Recognition of Closed-Eye Movements with Cameras in Smart Glasses
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A4 Artikkeli konferenssijulkaisussa
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Date
2019
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Language
en
Pages
13
322-334
322-334
Series
Advances in Computational Intelligence - 15th International Work-Conference on Artificial Neural Networks, IWANN 2019, Proceedings, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Volume 11506 LNCS
Abstract
Gaze gestures bear potential for user input with mobile devices, especially smart glasses, due to being always available and hands-free. So far, gaze gesture recognition approaches have utilized open-eye movements only and disregarded closed-eye movements. This paper is a first investigation of the feasibility of detecting and recognizing closed-eye gaze gestures from close-up optical sources, e.g. eye-facing cameras embedded in smart glasses. We propose four different closed-eye gaze gesture protocols, which extend the alphabet of existing open-eye gaze gesture approaches. We further propose a methodology for detecting and extracting the corresponding closed-eye movements with full optical flow, time series processing, and machine learning. In the evaluation of the four protocols we find closed-eye gaze gestures to be detected 82.8%-91.6% of the time, and extracted gestures to be recognized correctly with an accuracy of 92.9%-99.2%.Description
Keywords
Closed eyes, Gaze gestures, Machine learning, Mobile computing, Recognition, Smart glasses, Time series analysis
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Citation
Findling, R D, Nguyen, L N & Sigg, S 2019, Closed-Eye Gaze Gestures : Detection and Recognition of Closed-Eye Movements with Cameras in Smart Glasses . in I Rojas, G Joya & A Catala (eds), Advances in Computational Intelligence - 15th International Work-Conference on Artificial Neural Networks, IWANN 2019, Proceedings . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11506 LNCS, Springer, pp. 322-334, International Work Conference on Artificial Neural Networks, Gran Canaria, Spain, 12/06/2019 . https://doi.org/10.1007/978-3-030-20521-8_27