aSpaces : Action Spaces for Recognition and Synthesis of Human Actions

Human behavior analysis is an open problem in the computer vision community. The aim of this paper is to model human actions. We present a taxonomy in order to discuss about a knowledge-based classification of human behavior. A novel human action model is presented, called the aSpace, based on a Point Distribution Model (PDM). This representation is compact, accurate and specific. The human body model is represented as a stick figure, and several sequences of humans actions are used to compute the aSpace. In order to test our action representation, two applications are provided: recognition and synthesis of actions.

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