Adaptive surface reconstruction

Demetri Terzopoulos; Manuela Vasilescu

doi:10.1117/12.25262

1 April 1991 Adaptive surface reconstruction

Demetri Terzopoulos, Manuela Vasilescu

Proceedings Volume 1383, Sensor Fusion III: 3D Perception and Recognition; (1991) https://doi.org/10.1117/12.25262
Event: Advances in Intelligent Robotics Systems, 1990, Boston, MA, United States

Abstract

This paper introduces a new approach to surface reconstruction motivated by concepts from numerical grid generation. We develop adaptive mesh models that nonuniformly sample and reconstruct input shape data. Adaptive meshes are dynamic models assembled from nodal masses connected by adjustable springs. Acting as mobile sampling sites, the nodes observe interesting properties of the input data, such as depths, gradients, and curvatures. The springs automatically adjust their stiffnesses based on the locally sampled information in order to concentrate nodes near rapid shape variations. The representational power of an adaptive mesh is enhanced by its ability to optimally distribute the available degrees of freedom in accordance with the local complexity of the input data. Surface reconstruction using adaptive meshes runs at interactive rates with continuous 3D display on a graphics workstation.

Citation Download Citation

Demetri Terzopoulos and Manuela Vasilescu "Adaptive surface reconstruction", Proc. SPIE 1383, Sensor Fusion III: 3D Perception and Recognition, (1 April 1991); https://doi.org/10.1117/12.25262

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