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Decision-Theoretic Assistants Based on Contextual Gesture Recognition

  • José Antonio Montero
  • Luis E. Sucar
  • Miriam Martínez
Part of the Annals of Information Systems book series (AOIS, volume 19)

Abstract

This paper presents a novel approach that combines computer vision and decision theory for building intelligent assistants. It considers situations in which a person interacts with surrounding objects, where the system determines the most probable activity and based on it selects an action according to certain parameters. This framework is applicable to situations in which decisions are based on human activities and their interactions with objects in the environment. Examples of this type of situation include a caregiver that helps a handicapped person or an automatic video conference system that selects the best view according to the speaker’s actions. The system assumes that the human activity can be recognized based on hand gestures and their interaction with relevant objects present in the environment. The proposed approach combines contextual-based gesture recognition with a decision theoretic model for selecting the best action in uncertain conditions. Gesture recognition is based on hidden Markov models, combining motion and contextual information, where the context refers to the relative position of the hand to a nearby object. The posterior probability of each gesture is used in a Partially Observable Markov Decision Process (POMDP) to select the best action according to a utility function. The POMDP is implemented as a dynamic decision network (DDN). Experiments in two settings, videoconference and human care giving, show promising results in both gesture recognition and action selection. The experiments show that the proposed framework is robust to changes in the parameters (lookahead, probabilities and rewards), and shows that the performance is similar to that of a human assistant.

Keywords

POMDPs Dynamic decision networks Intelligent assistant Gesture recognition 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • José Antonio Montero
    • 1
  • Luis E. Sucar
    • 2
  • Miriam Martínez
    • 1
  1. 1.Acapulco Institute of TechnologyAcapulcoMexico
  2. 2.Department of Computer ScienceNational Institute of Astrophysics, Optics and ElectronicsTonanzintlaMexico

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