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Published August 2001 | public
Book Section - Chapter

Dynamic Real-Time Deformations using Space & Time Adaptive Sampling

Abstract

This paper presents a robust, adaptive method for animating dynamic visco-elastic deformable objects that provides a guaranteed frame rate. Our approach uses a novel automatic space and time adaptive level of detail technique, in combination with a large-displacement (Green) strain tensor formulation. The body is partitioned in a non-nested multiresolution hierarchy of tetrahedral meshes. The local resolution is determined by a quality condition that indicates where and when the resolution is too coarse. As the object moves and deforms, the sampling is refined to concentrate the computational load into the regions that deform the most. Our model consists of a continuous differential equation that is solved using a local explicit finite element method. We demonstrate that our adaptive Green strain tensor formulation suppresses unwanted artifacts in the dynamic behavior, compared to adaptive mass-spring and other adaptive approaches. In particular, damped elastic vibration modes are shown to be nearly unchanged for several levels of refinement. Results are presented in the context of a virtual reality system. The user interacts in real-time with the dynamic object through the control of a rigid tool, attached to a haptic device driven with forces derived from the method.

Additional Information

© 2001 ACM. The author would like to thank Eitan Grispun, Zoë Wood, and Mark Meyer for proof-reading and improving this paper. This work has been partially supported by the Rhône-Alpes region (EURODOC grant), the National Science Foundation (ASC-89-20219), as part of the STC for Computer Graphics and Scientific Visualization, and by the Integrated Media Systems Center, a NSF Engineering Research Center, Cooperative Agrement No. EEC-9529152.

Additional details

Created:
August 19, 2023
Modified:
October 20, 2023