Adaptive Keypose Extraction from Motion Capture Data (Preprint)

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概要

• 論文の詳細を見る

• In this paper, we present a novel method to extract keyposes from motion-capture data streams. It adaptively extracts keyposes in response to the motion characteristics of a given data stream. We adopt an approach to detect local minima in the temporal variation of motion speed. In the developed algorithm, the intensity of each local minimum is first evaluated by using a set of signals; it is obtained by applying a set of low-pass filters to a one-dimensional motion-speed data stream. The cut-off frequencies of the filters are distributed over a wide frequency range. By adding up the speed-descent values of each local minimum over all the signals, we exhaustively obtain the information on its intensity provided at all the time-scale levels covered by a given data stream. Then, the obtained intensity values are categorized by a clustering algorithm; the local minima categorized as those of little significance are deleted and the remaining ones are fixed as those giving keyposes. Experimental results showed that the present method provided results comparable to the best of those given by the methods previously proposed. This was achieved without readjusting the values of parameters used in the algorithm. Readjustment was indispensable for the other methods to obtain good results.------------------------------This is a preprint of an article intended for publication Journal ofInformation Processing(JIP). This preprint should not be cited. Thisarticle should be cited as: Journal of Information Processing Vol.22(2014) No.1 (online)------------------------------

• 2013-12-15

著者

• Takeshi Miura

  Graduate School of Engineering and Resource Science, Akita University

• Hideo Tamamoto

  Graduate School of Engineering and Resource Science, Akita University

• Takaaki Kaiga

  Graduate School Of Engineering And Resource Science Akita University | Digital Art Factory Warabi-za

• Hiroaki Katsura

  Faculty of Education and Human Studies, Akita University

• Katsubumi Tajima

  Graduate School of Engineering and Resource Science, Akita University

• Takeshi Shibata

  Venture Business Laboratory, Akita University

• Hideo Tamamoto

  Akita University

関連論文

• Adaptation of Grouping Structure Analysis in GTTM to Hierarchical Segmentation of Dance Motion
• Extraction of Motion Characteristics in Dances by Statistical Analysis of Joint Motions
• Indexing of Motion Capture Data Using Feature Vectors Derived from Posture Variation (Preprint)
• Adaptive Keypose Extraction from Motion Capture Data (Preprint)

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