Penalized-Distance Volumetric Skeleton Algorithm
IEEE Transactions on Visualization and Computer Graphics
Shock-Based Indexing into Large Shape Databases
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Normalized Gradient Vector Diffusion and Image Segmentation
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Skeleton Extraction of 3D Objects with Radial Basis Functions
SMI '03 Proceedings of the Shape Modeling International 2003
Skeleton Based Shape Matching and Retrieval
SMI '03 Proceedings of the Shape Modeling International 2003
Automatic Animation Skeleton Construction Using Repulsive Force Field
PG '03 Proceedings of the 11th Pacific Conference on Computer Graphics and Applications
The topology of symmetric, second-order tensor fields
VIS '94 Proceedings of the conference on Visualization '94
Snakes, shapes, and gradient vector flow
IEEE Transactions on Image Processing
Sketch-based 3D model retrieval using diffusion tensor fields of suggestive contours
Proceedings of the international conference on Multimedia
3D model retrieval using the histogram of orientation of suggestive contours
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part II
SHREC'12 track: sketch-based 3D shape retrieval
EG 3DOR'12 Proceedings of the 5th Eurographics conference on 3D Object Retrieval
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The understanding of object's kinematic structure is one of main challenges in the area of computer vision. Especially, skeleton of deformable objects, which is familiar with human visual perception, visualizes its characteristic using few data. This paper describes an efficient approach for automatic skeleton extraction and its splitting in the space of diffusion tensor fields, which are generated from normalized gradient vector flow fields of a given image. Our method is based on two steps: Skeleton extraction using second order diffusion tensor fields, Splitting skeleton using dissimilarity measure between neighbor elements. The evaluation proofs the efficiency of our technique which might be applied to object retrieval, pose estimation and action recognition, object registration and visualization.