Introducing a statistical behavior model into camera-based fall detection

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6453 LNCS, Issue PART 1, 2010, Pages 163-172

  Zweng, Andreas ^a   Zambanini, Sebastian ^a   Kampel, Martin ^a  

^a VIENNA UNIVERSITY OF TECHNOLOGY   (Austria)

Author keywords

[No Author keywords available]

Indexed keywords

ELDERLY PEOPLE; FALL DETECTION; MULTIPLE CAMERAS; SPATIO-TEMPORAL; STATISTICAL BEHAVIOR; VIDEO SEQUENCES; CAMERA-BASED; SPATIO TEMPORAL;

SEMANTICS; VIDEO CAMERAS;

CAMERAS;

EID: 78650768208     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-17289-2_16     Document Type: Conference Paper

References (18)

1. Grundy, E., Tomassini, C., Festy, P.: Demographic change and the care of older people: introduction. European Journal of Population 22, 215-218 (2006) (Pubitemid 44830313)
2. Wild, D., Nayak, U., Isaacs, B.: How dangerous are falls in old people at home? British Medical Journal 282, 266-268 (1981)
3. Cucchiara, R., Grana, C., Prati, A., Vezzani, R.: Probabilistic posture classification for human-behavior analysis. SMC-A: Systems and Humans 35, 42-54 (2005) (Pubitemid 40085385)
4. Anderson, D., Keller, J., Skubic, M., Chen, X., He, Z.: Recognizing falls from silhouettes. In: International Conference of the Engineering in Medicine and Biology Society, pp. 6388-6391 (2006)
5. Toreyin, B., Dedeoglu, Y., Çetin, A.: HMM based falling person detection using both audio and video. In: Sebe, N., Lew, M., Huang, T.S. (eds.) HCI/ICCV 2005. LNCS, vol. 3766, pp. 211-220. Springer, Heidelberg (2005)
6. Tao, J., Turjo, M., Wong, M., Wang, M., Tan, Y.: Fall incidents detection for intelligent video surveillance. In: Fifth International Conference on Information, Communications and Signal Processing, pp. 1590-1594 (2005)
7. Thome, N., Miguet, S., Ambellouis, S.: A Real-Time, Multiview Fall Detection System: A LHMM-Based Approach. IEEE TCSVT 18, 1522-1532 (2008)
8. Rougier, C., Meunier, J., St-Arnaud, A., Rousseau, J.: Monocular 3D head tracking to detect falls of elderly people. In: International Conference of the Engineering in Medicine and Biology Society, pp. 6384-6387 (2006)
9. Lin, C., Ling, Z., Chang, Y., Kuo, C.: Compressed-domain Fall Incident Detection for Intelligent Homecare. Journal of VLSI Signal Processing 49, 393-408 (2007)
10. Huang, C., Chen, E., Chung, P.: Fall detection using modular neural networks with back-projected optical flow. Biomedical Engineering: Applications, Basis and Communications 19, 415-424 (2007)
11. Anderson, D., Luke, R., Keller, J., Skubic, M., Rantz, M., Aud, M.: Linguistic summarization of video for fall detection using voxel person and fuzzy logic. Computer Vision and Image Understanding 113, 80-89 (2009)
12. Nater, F., Grabner, H., Van Gool, L.: Exploiting simple hierarchies for unsupervised human behavior analysis. In: International Conference on Computer Vision and Pattern Recognition (2010) (to appear)
13. Nait-Charif, H., McKenna, S.: Activity summarisation and fall detection in a supportive home environment. In: International Conference on Proceedings of the Pattern Recognition, vol. 4, pp. 323-326 (2004)
14. Wren, C., Azarbayejani, A., Darrell, T., Pentland, A.: Pfinder: Real-time tracking of the human body. PAMI 19, 780-785 (1997)
15. Kampel, M., Hanbury, A., Blauensteiner, P., Wildenauer, H.: Improved motion segmentation based on shadow detection 6, 1-12 (2007)
16. Zadeh, L.: Fuzzy sets. Information and Control 8, 338-353 (1965)
17. Ermis, E., Saligrama, V., Jodoin, P.M., Konrad, J.: Abnormal behavior detection and behavior matching for networked cameras. In: Second ACM/IEEE International Conference on Distributed Smart Cameras, pp. 1-10 (2008)
18. Noury, N., Fleury, A., Rumeau, P., Bourke, A., Laighin, G., Rialle, V., Lundy, J.: Fall detection - Principles and methods. In: International Conference of the Engineering in Medicine and Biology Society, pp. 1663-1666 (2007)