Unsupervised Segmentation of Human Motion Data Using a Sticky Hierarchical Dirichlet Process-Hidden Markov Model and Minimal Description Length-Based Chunking Method for Imitation Learning

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概要

• 論文の詳細を見る
• 2011-11-01

著者

• Iwahashi Naoto

  National Institute Of Information And Communications Technology

• TANIGUCHI Tadahiro

  Ritsumeikan University

• HAMAHATA Keita

  Ritsumeikan Univeirsity

関連論文

• Learning, Generation and Recognition of Motions by Reference-Point-Dependent Probabilistic Models
• Interactive Learning of Spoken Words and Their Meanings Through an Audio-Visual Interface
• Preface
• Situated Spoken Dialogue with Robots Using Active Learning
• Unsupervised Segmentation of Human Motion Data Using a Sticky Hierarchical Dirichlet Process-Hidden Markov Model and Minimal Description Length-Based Chunking Method for Imitation Learning

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