Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Spectral Feature Vectors for Graph Clustering
Proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Multiclass Spectral Clustering
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Dominant Sets and Hierarchical Clustering
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Pattern Vectors from Algebraic Graph Theory
IEEE Transactions on Pattern Analysis and Machine Intelligence
Complex Fiedler Vectors for Shape Retrieval
SSPR & SPR '08 Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Graph clustering using the weighted minimum common supergraph
GbRPR'03 Proceedings of the 4th IAPR international conference on Graph based representations in pattern recognition
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In this paper we use the spectra of a Hermitian matrix and the coefficient of the symmetric polynomials to cluster different human poses taken by an inexpensive 3D camera, the Microsoft 'Kinect' for XBox 360. We construct a Hermitian matrix from the joints and the angles subtended by each pair of limbs using the three-dimensional 'skeleton' data delivered by Kinect. To compute the angles between a pair of limbs we construct the line graph from the given skeleton. We construct pattern vectors from the eigenvectors of the Hermitian matrix. The pattern vectors are embedded into a pattern-space using Principal Component Analysis (PCA). We compere the results obtained with the Laplacian spectra pattern vectors. The empirical results show that using the angular information can be efficiently used to clusters different human poses.