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Título del libro: 2013 16th International Conference On Advanced Robotics (icar)
Título del capítulo: Recognition of Arm Activities Based on Hidden Markov Models for Natural Interaction with Service Robots

Autores UNAM:
JOSE ISRAEL FIGUEROA ANGULO; JESUS SAVAGE CARMONA; ERNESTO BRIBIESCA CORREA; BORIS ESCALANTE RAMIREZ; RONALD STUART LEDER;
Autores externos:

Idioma:

Año de publicación:
2013
Palabras clave:

Hidden Markov Models; Activity Recognition; Motion Recognition; Human-Machine Interaction; Pattern Recognition; Machine Learning; Viterbi Path


Resumen:

This research presents a novel way of representing human motion and recognizing human activities from the skeleton output computed from RGB-D data from vision-based motion capture systems. The method uses a representation of the skeleton which is invariant to rotation and translation, based on Orthogonal Direction Change Chain Codes, as observations for a single Discrete Connected Hidden Markov Model formed by a set of multiple Hidden Markov Models for simple activities, which are merged using a grammar-based structure. The purpose of this research is to provide a service robot with the capability of human activity awareness, which can be used for action planning with implicit and indirect Human-Robot Interaction.


Entidades citadas de la UNAM: