Robust fall detection using human shape and multi-class support vector machine

Proceedings - 6th Indian Conference on Computer Vision, Graphics and Image Processing, ICVGIP 2008

Volumn , Issue , 2008, Pages 413-420

  Foroughi, Homa ^a   Rezvanian, Alireza ^b   Paziraee, Amirhossien ^c  

^a FERDOWSI UNIVERSITY OF MASHHAD   (Iran)

^b ISLAMIC AZAD UNIVERSITY   (Iran)

^c ISLAMIC AZAD UNIVERSITY   (Iran)

Author keywords

[No Author keywords available]

Indexed keywords

ABNORMAL BEHAVIORS; DAILY LIFE ACTIVITIES; FALL DETECTIONS; FEATURE VECTORS; HEAD POSE; HUMAN BODIES; HUMAN FALL DETECTIONS; INDEPENDENT LIVINGS; INTELLIGENT VIDEO SURVEILLANCES; MOVEMENT PATTERNS; MULTI-CLASS SUPPORT VECTOR MACHINES; PROJECTION HISTOGRAMS; RANGE OF MOTIONS; RELIABLE RECOGNITION; SHAPE VARIATIONS; TEMPORAL CHANGES;

COMPUTER VISION; HEALTH HAZARDS; IMAGE RETRIEVAL; IMAGING SYSTEMS; SECURITY SYSTEMS;

SUPPORT VECTOR MACHINES;

EID: 65249118707     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICVGIP.2008.49     Document Type: Conference Paper

References (15)

1. N Noury, A Fleury, P Rumeau, A Bourke, G Laighin, V Rialle, J Lundy "Fall detection - Principles and Methods" Conf Proc IEEE Eng Med Biol Soc. 2007 ;1 :1663-1666 18002293 (P,S,E,B)
2. Arie Hans Nasution and S. Emmanuel; Intelligent Video Surveillance for Monitoring Elderly in Home Environments, International Workshop on Multimedia Signal Processing (MMSP), Greece, October 2007.
3. Sixsmith A, Johnson N. "Smart sensor to detect the falls of the elderly", IEEE Pervasive Computing, vol. 3, no. 2, pp. 42-47, April-June 2004.
4. Caroline Rougier, Jean Meunier, Alain St-Arnaud, Jacqueline Rousseau, "Fall Detection from Human Shape and Motion History Using Video Surveillance" Advanced Information Networking and Applications Workshops, 2007, AINAW '07. 21st International Conference on, Vol. 2 (2007), pp. 875-880.
5. B. T̈oreyin, Y. Dedeoglu, and A. Ç etin. Hmm based falling person detection using both audio and video. In IEEE International Workshop on Human-Computer Interaction, Beijing, China, 2005.
6. S.-G.Miaou, P.-H. Sung, and C.-Y. Huang, "A Customized Human Fall Detection System Using Omni- Camera Images and Personal Information" Proc of Distributed Diagnosis and Home Healthcare(D2H2) Conference, 2006
7. R. Cucchiara, A.Pratti, and R.Vezani, "An Intelligent Surveillance System for Dangerous Situation Detection in home Environments" , in Intelligenza artificable, vol.1, n.1, pp. 11-15, 2004
8. T. Lee and A. Mihailidis. An intelligent emergency response system: preliminary development and testing of automated fall detection. Journal of telemedicine and telecare, 11(4):194-198, 2005.
9. Nait CH, McKenna SJ. "Activity summarisation and fall detection in a supportive home environment", Int. Conf. on Pattern Recognition (ICPR), 2004.
10. Tao, J., M.Turjo, M.-F. Wong, M.Wang and Y.-P Tan, "Fall Incidents Detection for Intelligent Video Surveillance" , ICICS2005
11. C.Rougier, J.Meunier, A. St-Arnaud, J.Rousseau, "Monocular 3D Head Tracking to Detect Falls of Elderly People", International Conference of IEEE Engineering in Medicine and Biology Society, Sept 2006
12. Hsu, C.W. and Lin, C.J. "A Comparison of Methods for Multi-class Support Vector Machines," IEEE transaction on Neural Networks. Vol. 13. No.2. pp 415- 425, 2002
13. Kreβ el, U., Pairwise classification and support vector machines, In Advances in Kernel Methods-Support Vector Learning, Cambridge, MA: MIT Press, 1999.
14. J.C.Platt, N. Cristianini and J.Shawe-Taylor "Large Margin DAGs for Multiclass Classification" In Advances in Neural Information Processing Systems. Vol 12, pages 547-553, MIT Press, 2000
15. K. Kim, T. Chalidabhongse, D. Harwood, and L. Davis. Real-time foreground-background segmentation using codebook model. Real-Time Imaging, 11(3):172--185, June 2005.