Abstract
We present an eating activity detection method via automatic detecting dining plates from images acquired chronically by a wearable camera. Convex edge segments and their combinations within each input image are modeled with respect to probabilities of belonging to candidate ellipses. Then, a dining plate is determined according to a confidence score. Finally, the presence/absence of an eating event in an image sequence is determined by analyzing successive frames. Our experimental results verified the effectiveness of this method.
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Schedule a callMore From: SenseCam 2013 : proceedings of the 4th SenseCam Conference : SenseCam and Pervasive Imaging 2013 : San Diego, USA, November 18-19, 2013. SenseCam (Conference) (4th : 2013 : San Diego, Calif.)
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