Title page for ETD etd-06192009-152207


Type of Document Master's Thesis
Author Xie, Liguang
Author's Email Address xie@vt.edu
URN etd-06192009-152207
Title Realistic Motion Estimation Using Accelerometers
Degree Master of Science
Department Computer Science
Advisory Committee
Advisor Name Title
Cao, Yong Committee Chair
Ehrich, Roger W. Committee Member
Quek, Francis K. H. Committee Member
Keywords
  • Locally linear embedding
  • Performance animation
  • Optimization
  • Motion synthesis
  • Accelerometers
  • Interpolation
Date of Defense 2009-06-18
Availability restricted
Abstract
A challenging goal for both the game industry and the research community of computer graphics is the generation of 3D virtual avatars that automatically perform realistic human motions with high speed at low monetary cost. So far, full body motion estimation of human complexity remains an important open problem. We propose a realistic motion estimation framework to control the animation of 3D avatars. Instead of relying on a motion capture device as the control signal, we use low-cost and ubiquitously available 3D accelerometer sensors. The framework is developed in a data-driven fashion, which includes two phases: model learning from an existing high quality motion database, and motion synthesis from the control signal. In the phase of model learning, we built a high quality motion model of less complexity that learned from a large motion capture database. Then, by taking the 3D accelerometer sensor signal as input, we were able to synthesize high-quality motion from the motion model we learned.

In this thesis, we present two different techniques for model learning and motion synthesis, respectively. Linear and nonlinear reduction techniques for data dimensionality are applied to search for the proper low dimensional representation of motion data. Two motion synthesis methods, interpolation and optimization, are compared using the 3D acceleration signals with high noise. We evaluate the result visually compared to the real video and quantitatively compared to the ground truth motion. The system performs well, which makes it available to a wide range of interactive applications, such as character control in 3D virtual environments and occupational training.

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