@INPROCEEDINGS{0796Goldmann2004,
	AUTHOR = {Lutz Goldmann and Mustafa Karaman and Thomas Sikora},
	TITLE = {Human Body Posture Recognition Using MPEG-7 Descriptors},
	BOOKTITLE = {IS&T/SPIE's Electronic Imaging 2004},
	YEAR = {2004},
	MONTH = jan,
	ADDRESS = {San Jose, CA, USA.},
	PDF = {http://elvera.nue.tu-berlin.de/files/0796Goldmann2004.pdf},
	URL = {http://elvera.nue.tu-berlin.de/files/0796Goldmann2004.pdf},
	ABSTRACT = {This paper presents a novel approach to human body posture recognition based on the MPEG-7 contour-based shape descriptor and the widely used projection histogram. A combination of them was used to recognize the main posture and the view of a human based on the binary object mask obtained by the segmentation process. The recognition is treated as a typical pattern recognition task and is carried out through a hierarchy of classifiers. Therefore various structures both hierachical and non-hierarchical, in combination with different classifiers, are compared to each other with respect to recognition performance and computational complexity. Based on this an optimal system design with recognition rates of 95.59% for the main posture, 77.84% for the view and 79.77% in combination is achieved.}
}