One class boundary method classifiers for application in a video-based fall detection system

IET Computer Vision

Volumn 6, Issue 2, 2012, Pages 90-100

  Yu, M ^a   Naqvi, S M ^a   Rhuma, A ^a   Chambers, J ^a  

^a LOUGHBOROUGH UNIVERSITY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

BOUNDARY METHOD; CLASS BOUNDARY; COMPARISON RESULT; COMPUTATIONAL TIME; DATA SETS; FALL DETECTION; FALSE POSITIVE RATES; FEATURE SPACE; GEOMETRIC MEAN; MINIMAX PROBABILITY MACHINE; NEAREST NEIGHBOUR; ONE-CLASS CLASSIFICATION TECHNIQUES; ONE-CLASS SUPPORT VECTOR MACHINE; SMART ROOMS; THREEDIMENSIONAL (3-D); TRAINING DATASET; TRUE POSITIVE RATES; VIDEO FEATURES; VIDEO-BASED FALL DETECTION; VOXEL PERSON;

COMPUTER SCIENCE; COMPUTER VISION; SOFTWARE ENGINEERING;

FACE RECOGNITION;

EID: 84858720456     PISSN: 17519632     EISSN: 17519640     Source Type: Journal    
DOI: 10.1049/iet-cvi.2011.0046     Document Type: Article

References (21)

1. http://www.medicalnewstoday.com/articles/142487.php, accessed April 2011
2. Bourke, A., Scanaill, C., Culhane, K., O'Brien, J., and Lyons, G.: 'An optimum accelerometer configuration and simple algorithm for accurately detecting falls', Proc. 24th IASTED Int. Conf. on Biomedical Engineering, Anaheim, CA, USA 2006, p. 156-160
3. Kangas, M., Konttila, A., Lindgren, P., Winblad, I., and Jamsa, T.: 'Comparison of low-complexity fall detection algorithms for body attached accelerometers', Gait Posture, 2008, 28, (2), p. 285-29110.1016/j.gaitpost.2008.01.003
4. Alwan, M., Rajendran, P., and Kell, S.: et al. 'A smart and passive floor-vibration based fall detector for elderly', Second IEEE Int. Conf. on Information and Communication Technologies: from Theory to Applications, Damascus, Syria, April 2006
5. Rougier, C., and Meunier, J.: 'A. St-Arnaud, and J. Rousseau, 'Monocular 3d head tracking to detect falls of elderly people', Proc. 28th Int. Conf. of the IEEE Engineering in Medicine and Biology Society, New York, USA, September 2006, p. 6384-6387
6. Rougier, C., Meunier, J., St-Arnaud, A., and Rousseau, J.: 'Fall detection from human shape and motion history using video surveillance', Proc. 21st Int. Conf. on Advanced Information Networking and Applications Workshops, Niagara Falls, Canada, May 2007, p. 875-880
7. Juang, C., and Chang, C.: 'Human body posture classification by a neural fuzzy network and home care system application', IEEE Trans. Syst., Man Cybern. A, Syst. Humans, 2007, 37, (6), p. 984-99410.1109/TSMCA.2007.897609 1083-4427
8. Foroughi, H., Rezvanian, A., and Paziraee, A.: 'Robust fall detection using human shape and multi-class support vector machine', Proc. Sixth Indian Conf. on Computer Vision, Graphics and Image Processing, December 2008, p. 413-420
9. Thome, N., Miguet, S., and Ambellouis, S.: 'A real-time, multiview fall detection system: a lhmm-based approach', IEEE Trans. Circuits Syst. Video Technol., 2008, 19, (10), p. 1522-153210.1109/TCSVT.2008.2005606 1051-8215
10. Tax, D.: 'One-class classification', 2001, PhD, TU Delft, The Netherlands
11. Anderson, D., Luke, R., Keller, J., Skubic, M., Rantz, M., and Aud, M.: 'Modeling human activity from voxel person using fuzzy logic', IEEE Trans. Fuzzy Syst., 2009, 17, (1), p. 39-4910.1109/TFUZZ.2008.2004498 1063-6706
12. Zambanini, S., Machajdik, J., and Kampel, M.: 'Early versus late fusion in a multiple camera network for fall detection', Proc. 34th Annual Workshop of the Austrian Association for Pattern Recognition, Zwettl, Austria, May 2010, p. 15-22
13. Kim, K., Chalidabhongse, T., Harwood, D., and Davis, L.: 'Real-time foreground-background segmentation using code-book model', Real-Time Imaging, 2005, 11, (3), p. 172-18510.1016/j.rti.2004.12.004 1077-2014
14. Stauffer, C., and Grimson, W.: 'Adaptive background mixture models for real-time tracking', IEEE Int. Conf. on Computer Vision and Pattern Recognition, Fort Collins, USA, June 1999
15. Elgammal, A., Harwood, D., and Davis, L.: 'Non-parametric model for background subtraction', Proc. European Conf. on Computer Vision 2000, Dublin, Ireland, July 2000, p. 751-767
16. Tsai, R.: 'A versatile camera calibration technique for high-accuracy 3d machine vision metrology using off-the-shelf TV cameras and lenses', IEEE J. Robot. Autom., 1987, 3, (4), p. 323-34410.1109/JRA.1987.1087109 0882-4967
17. Strang, G.: 'Introduction to linear algebra', 4th(Wellesley-Cambridge Press and SIAM 2009)
18. Scholkopf, B., Platt, J., Taylor, J., Smola, A., and Williamson, R.: 'Estimating the support of a high-dimensional distribution', Neural Comput., 2001, 13, (7), p. 1443-147110.1162/089976601750264965 0899-7667
19. Boyd, S., and Vandenberghe, L.: 'Convex optimization', 1st(Cambridge University Press 2004)
20. Lanckriet, G., Ghaoui, L., Bhattacharyya, C., and Jordan, M.: 'Robust novelty detection with single-class mpm', Proc. Neural Information Processing Systems, Whistler, British Columbia, Canada 2002, p. 905-912
21. Yu, X.: 'Approaches and principles of fall detection for elderly and patient', Proc. Tenth IEEE Int. Conf. on e-Health Networking, Applications and Services, Singapore, July 2008, p. 42-47