Data-Driven Reconstruction of Human Locomotion Using a Single Smartphone

• Published in: Computer graphics forum Vol. 33; no. 7; pp. 11 - 19
• Main Authors: Eom, Haegwang, Choi, Byungkuk, Noh, Junyong
• Format: Journal Article
• Language: English
• Published: Oxford Blackwell Publishing Ltd 01.10.2014
• Subjects: Analysis; Categories and Subject Descriptors (according to ACM CCS); Computer graphics; Human body; I.3.7 [Three-Dimensional Graphics and Realism]: Animation; Motion capture; Movement; Sensors; Smartphones; Studies
• ISSN: 0167-7055; 1467-8659
• DOI: 10.1111/cgf.12469

Generating a visually appealing human motion sequence using low‐dimensional control signals is a major line of study in the motion research area in computer graphics. We propose a novel approach that allows us to reconstruct full body human locomotion using a single inertial sensing device, a smartphone. Smartphones are among the most widely used devices and incorporate inertial sensors such as an accelerometer and a gyroscope. To find a mapping between a full body pose and smartphone sensor data, we perform low dimensional embedding of full body motion capture data, based on a Gaussian Process Latent Variable Model. Our system ensures temporal coherence between the reconstructed poses by using a state decomposition model for automatic phase segmentation. Finally, application of the proposed nonlinear regression algorithm finds a proper mapping between the latent space and the sensor data. Our framework effectively reconstructs plausible 3D locomotion sequences. We compare the generated animation to ground truth data obtained using a commercial motion capture system.