Abstract
Google Glass has potential to be a real-time data capture and annotation tool. With professional sports as a use-case, we present a platform which helps a football coach capture and annotate interesting events using Google Glass. In our implementation, an interesting event is indicated by a predefined hand gesture or motion, and our platform can automatically detect these gestures in a video without training any classifier. Three event detectors are examined and our experiment shows that the detector with combined edgeness and color moment features gives the best detection performance.
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Zhou, J., Duane, A., Albatal, R., Gurrin, C., Johansen, D. (2015). Wearable Cameras for Real-Time Activity Annotation. In: He, X., Luo, S., Tao, D., Xu, C., Yang, J., Hasan, M.A. (eds) MultiMedia Modeling. MMM 2015. Lecture Notes in Computer Science, vol 8936. Springer, Cham. https://doi.org/10.1007/978-3-319-14442-9_38
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DOI: https://doi.org/10.1007/978-3-319-14442-9_38
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-14441-2
Online ISBN: 978-3-319-14442-9
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