Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/91743
Title: EOG-cased ocular and gaze angle estimation using an extended Kalman filter
Authors: Barbara, Nathaniel
Camilleri, Tracey A.
Camilleri, Kenneth P.
Keywords: Electrooculography
Brain-computer interfaces
Human-computer interaction
Eye contact
Eye tracking
Eye -- Movement
Eye -- Movement -- Photographic measurements
Issue Date: 2020
Publisher: ACM
Citation: Barbara, N., Camilleri, T. A., & Camilleri, K. P. (2020, June). EOG-cased ocular and gaze angle estimation using an extended Kalman filter. In ACM Symposium on Eye Tracking Research and Applications (pp. 1-5).
Abstract: In this work, a novel method to estimate the ocular pose from electrooculography (EOG) signals is proposed. This method is based on an electrical battery model of the eye which relates the EOG potential to the distances between an electrode and the left/right cornea and retina centre points. In this work, this model is used to estimate the ocular angles (OAs), that is the orientation of the two ocular globes separately. Using this approach, an average cross-validated horizontal and vertical OA estimation error of 2.91 ± 0.86° and 2.42 ± 0.58° respectively was obtained. Furthermore, we show how these OA estimates may be used to estimate the gaze angles (GAs) without requiring the distance between the subject’s face-plane and the target-plane, as in previous work. Using the proposed method, a cross-validated horizontal and vertical GA estimation error of 2.13 ± 0.73° and 2.42 ± 0.58° respectively was obtained, which compares well with the previous distance-based GA estimation technique.
URI: https://www.um.edu.mt/library/oar/handle/123456789/91743
Appears in Collections:Scholarly Works - FacEngSCE

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