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In this work, we propose an approach that relies on cues from depth perception from RGB-D images, where features related to human body motion (3D skeleton features) are used on multiple learning classifiers in order to recognize human activities on a benchmark dataset. A Dynamic Bayesian Mixture Model (DBMM) is designed to combine multiple classifier likelihoods into a single form, assigning weights...
This paper proposes a Kinect-based calling gesture recognition scenario for taking order service of an elderly care robot. The proposed scenarios are designed mainly for helping non expert users like elderly to call service robot for their service request. In order to facilitate elderly service, natural calling gestures are designed to interact with the robot. Our challenge here is how to make the...
For service robots to be able to enter a multi-human office environment, it is important to find a group of human users' social patterns and then to provide a proper service to them in time. Usually, human users' social patterns are represented in terms of nonverbal social signals. In this paper, a new integrated approach on recognizing multi-human social signals is proposed. Specifically, the nonverbal...
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