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arXiv · 1509.09014

Stats-Calculus Pose Descriptor Feeding A Discrete HMM Low-latency Detection and Recognition System For 3D Skeletal Actions

Rofael Emil Fayez Behnam
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Abstract

Recognition of human actions, under low observational latency, is a growing interest topic, nowadays. Many approaches have been represented based on a provided set of 3D Cartesian coordinates system originated at a certain specific point located on a root joint. In this paper, We will present a statistical detection and recognition system using Hidden Markov Model using 7 types of pose descriptors. * Cartesian Calculus Pose descriptor. * Angular Calculus Pose descriptor. * Mixed-mode Stats-Calculus Pose descriptor. * Centro-Stats-Calculus Pose descriptor. * Rela-Centro-Stats-Calculus Pose descriptor. * Rela-Centro-Stats-Calculus DCT Pose descriptor. * Rela-Centro-Stats-Calculus DCT-AMDF Pose descriptor. Stats-Calculus is a feature extracting technique, that is developed on Moving Pose descriptor , but using a combination of Statistics measures and Calculus measures.

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Rofael Emil Fayez Behnam. 2015-09-30. Stats-Calculus Pose Descriptor Feeding A Discrete HMM Low-latency Detection and Recognition System For 3D Skeletal Actions. https://arxiv.org/abs/1509.09014

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