| Conference/Proceedings | IS&T/SPIE's Electronic Imaging 2004 |
| Start date | 18.01.2004 |
| End date | 22.01.2004 |
| Address | San Jose, CA, USA. |
| Author(s) | Lutz Goldmann, Mustafa Karaman, Thomas Sikora |
| Title | Human Body Posture Recognition Using MPEG-7 Descriptors |
| 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. |
| Key words | sensing people, posture recognition, action recognition, projection histogram, MPEG-7 contour based shape descriptor, minimum distance classifier, k-nearest neighbor classifier |
| File | 0796Goldmann2004.pdf |