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Capture Database through Symbolization, Recognition and Generation of Motion Patterns

Motion capture systems are used to obtain motion data such that humanoid robots or computer graphics (CG) characters can behave naturally. However, it has proven to be hard not only to modify the capture data without losing its reality but also to search for the required capture data in a lot of capture data. In this paper, we provide a solution to these problems based on our previous work on symbolization of motion patterns for developing humanoid intelligence. Similar motion sequences in the database are abstracted as a symbol, which will be applied to searching motion patterns in the database similar to a given motion. This paper also introduces a method for building a stochastic symbol-word mapping model utilizing the word labels provided by the operator during motion capture sessions. This model converts a input sequence of words into a sequence of symbols, and then allows the capture database both to be searched for capture data corresponding to the input (a sequence of words) and to provide the users with new motion data generated by the symbols. Finally, we apply analogy of symbols to establishing the database in order to provide an appropriate motion data in response to an unsupervised sequence of words and then demonstrate the validity of analogy theory.