Level set diagrams of polyhedral objects
Proceedings of the fifth ACM symposium on Solid modeling and applications
Topology matching for fully automatic similarity estimation of 3D shapes
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Chord-to-point distance accumulation and planar curvature: a new approach to discrete curvature
Pattern Recognition Letters
SMI '04 Proceedings of the Shape Modeling International 2004
Interactive Skeleton Extraction Using Geodesic Distance
ICAT '06 Proceedings of the 16th International Conference on Artificial Reality and Telexistence--Workshops
Harmonic skeleton for realistic character animation
SCA '07 Proceedings of the 2007 ACM SIGGRAPH/Eurographics symposium on Computer animation
The Smoothed 3D Skeleton for Animation
NCM '09 Proceedings of the 2009 Fifth International Joint Conference on INC, IMS and IDC
Occluded 3d object recognition using partial shape and octree model
ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part I
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A 3D skeleton is a one-voxel thick, graph-like structure, widely used in the area of a character animation. In this paper, we propose a novel method for the 3D skeleton extraction of the polyhedral models based on a priori knowledge of the learned skeleton. The method has several steps. First, the octree of the input model is calculated and used to compare with the octree of the 3D models stored in the octrees database. By comparing the octree similarities, if the searched results exactly match with the input octree, the corresponding skeleton will be retrieved from the skeletons database. Otherwise, the method finds the list of the close match (the octree similarity ratio which the value is greater than 0.8) in order to use to estimate the new skeleton. In the worst case, if the input octree does not match with any case in the octrees database, the method computes the new skeleton and stores it in the skeletons database. The method is fast and efficient because it is not necessary to extract the skeleton from every input model. Thus, the computational time of our method depends only on the time of the octree similarity calculation, and the time for searching the similar octree in the octrees database. Several examples show the results obtained with our approach.