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Automatic skeleton extraction and splitting of target objects

: Yoon, Sang Min; Graf, Holger


Institute of Electrical and Electronics Engineers -IEEE-; IEEE Signal Processing Society:
16th IEEE International Conference on Image Processing, ICIP 2009. Proceedings. Vol.4 : Cairo, Egypt, 7 - 10 November 2009
Piscataway, NJ: IEEE, 2009
ISBN: 978-1-4244-5653-6 (Print)
ISBN: 978-1-4244-5654-3
ISBN: 978-1-4244-5655-0 (USB-Stick)
International Conference on Image Processing (ICIP) <16, 2009, Cairo>
Fraunhofer IGD ()
skeleton; deformable objects; feature extraction

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.