Human motion database with a binary tree and node transition graphs

— Database of human motion has been widely used for recognizing human motion and synthesizing humanoid motions. In this paper, we propose a data structure for storing and extracting human motion data and demonstrate that the database can be applied to the recognition and motion synthesis problems in robotics. We develop an efficient method for building a binary tree data structure from a set of continuous, multi-dimensional motion clips. Each node of the tree represents a statistical distribution of a set of human figure states extracted from the motion clips. We also identify the valid transitions among the nodes and construct node transition graphs. Similar states in different clips may be grouped into a single node, thereby allowing transitions between different behaviors. Using databases constructed from real human motion data, we demonstrate that the proposed data structure can be used for human motion recognition, state estimation and prediction, and robot motion planning.

• Type: Journal
• Year: 2011
• Where: AROBOTS
• Authors: Katsu Yamane, Yoshifumi Yamaguchi, Yoshihiko Nakamura
• Keywords: AROBOTS 2011, Data Structure, Human Motion, Human Motion Data, Software Engineering