Model Driven Segmentation of Articulating Humans in Laplacian Eigenspace

We propose a general approach using Laplacian Eigenmaps and a graphical model of the human body to segment 3D voxel data of humans into different articulated chains. In the bottom-up stage, the voxels are transformed into a high-dimensional (6D or less) Laplacian Eigenspace (LE) of the voxel neighbo...

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Veröffentlicht in:	IEEE transactions on pattern analysis and machine intelligence 2008-10, Vol.30 (10), p.1771-1785
Hauptverfasser:	Sundaresan, A., Chellappa, R.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Application software Applied sciences Articulated Artificial Intelligence Biological system modeling Cameras Computer science control theory systems Computer Simulation Exact sciences and technology Graph-theoretic methods Graphs Human Human body Humans Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Image Processing and Computer Vision Image segmentation Imaging, Three-Dimensional - methods Joints Joints - anatomy & histology Laplace equations Limbs Models, Anatomic Motion estimation partitioning Pattern Recognition Pattern Recognition, Automated - methods Pattern recognition. Digital image processing. Computational geometry Region growing Reproducibility of Results Segmentation Sensitivity and Specificity Splines Streaming media Studies Surveillance Three dimensional Whole Body Imaging - methods
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