Linear-projection-based classification of human postures in time-of-flight data

Authors:
Folker Wientapper;Katrin Ahrens;Harald Wuest;Ulrich Bockholt
Affiliations:
Department for Virtual and Augmented Reality, Fraunhofer IGD, Darmstadt, Germany;Department for Virtual and Augmented Reality, Fraunhofer IGD, Darmstadt, Germany;Department for Virtual and Augmented Reality, Fraunhofer IGD, Darmstadt, Germany;Department for Virtual and Augmented Reality, Fraunhofer IGD, Darmstadt, Germany
Venue:
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Year:
2009

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Abstract

This paper presents a simple yet effective approach for classification of human postures by using a time-of-flight camera. We investigate and adopt linear projection techniques such as Locality Preserving Projections (LPP), Linear Discriminant Analysis (LDA) and Principal Component Analysis (PCA), which are more widespread in face recognition and other pattern recognition tasks.We analyze the relations between LPP and LDA and show experimentally that using LPP in a supervised manner effectively yields very similar results as LDA, implying that LPP may be regarded as a generalization of LDA. Features for offline training and online classification are created by adopting common image processing techniques such as background-subtraction and blob detection to the time-of-flight data.