Germán González Serrano

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There is currently a division between real-world human performance and the decision making of socially interactive robots. This circumstance is partially due to the difficulty in estimating human cues, such as pose and gesture, from robot sensing. Towards bridging this division, we present a method for kinematic pose estimation and action recognition from(More)
A method is presented for kinematic pose estimation and action recognition from monocular robot vision through the use of dynamical human motion vocabularies. We propose the utilization of dynamical motion vocabularies towards bridging the decision making of observed humans and information from robot sensing. Our motion vocabulary is comprised of learned(More)
Perceiving human motion and non-verbal cues is an important aspect of human-robot interaction (Fong et al., 2002). For robots to become functional collaborators in society, they must be able to make decisions based on their perception of human state. Additionally, knowledge about human state is crucial for robots to learn control policies from direct(More)
We present a method for 3D monocular kinematic pose estimation and activity recognition through the use of dynamical human motion vocabularies. A motion vocabulary is comprised as a set of primitives that each describe the movement dynamics of an activity in a low-dimensional space. Given image observations over time, each primitive is used to infer the(More)
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