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Issue No.01 - January-March (2011 vol.10)
pp: 82-89
Hana Na , LG Electronics
Sheng-Feng Qin , Brunel University
David K. Wright , Brunel University
Preventing accidental injuries of toddlers requires thorough, consistent supervision, but this isn't always practical. A proposed vision-based system detects three fall risk factors in the home environment to help caregivers supervise nearby toddlers when they can't give continuous attention to the toddlers. The crucial technical challenge is to differentiate a human from other foreground objects in the images. Unlike previous systems, this one uses multiple dynamic motion cues for human detection, employing cues related to human appearance.
real-time systems, implementation, pattern recognition, computing methodologies, image processing and computer vision, computing methodologies, health, life and medical sciences, computer applications, pervasive computing
Hana Na, Sheng-Feng Qin, David K. Wright, "Detecting Fall Risk Factors for Toddlers", IEEE Pervasive Computing, vol.10, no. 1, pp. 82-89, January-March 2011, doi:10.1109/MPRV.2010.19
1. "Home Accidents," Child Accident Prevention Trust, Jan. 2008; .
2. A.G. Hauptmann et al., "Automated Analysis of Nursing Home Observations," IEEE Pervasive Computing, vol. 3, no. 2, 2004, pp. 15−21.
3. A. Sixsmith and N. Johnson, "A Smart Sensor to Detect the Falls of the Elderly," IEEE Pervasive Computing, vol. 3, no. 2, 2004, pp. 42−47.
4. M.N. Nyan, F.E.H. Tay, and M.Z.E. Mah, "Application of Motion Analysis System in Pre-impact Fall Detection," J. Biomechanics, vol. 41, no. 10, 2008, pp. 2297−2304.
5. L. Wang, W. Hu, and T. Tan, "Recent Developments in Human Motion Analysis," Pattern Recognition, vol. 36, no. 3, 2003, pp. 585−601.
6. P. Fihl et al., "Tracking of Individuals in Very Long Video Sequences," Advances in Visual Computing, LNCS 4291, Springer, 2006, pp. 60−69.
7. G. Medioni et al., "Robust Real-Time Vision for a Personal Service Robot," Computer Vision and Image Understanding, vol. 108, nos. 1−2, 2007, pp. 196−203.
8. B. Fan and Z.F. Wang, "Pose Estimation of Human Body Based on Silhouette Images," Proc. Int'l Conf. Information Acquisition, IEEE Press, 2004, pp. 296−300.
9. J. Shi and C. Tomasi, "Good Features to Track," Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR 94), IEEE Press, 1994, pp. 593−600.
10. B.D. Lucas and T. Kanade, "An Iterative Image Registration Technique with an Application to Stereo Vision," Proc. 17th Int'l Joint Conf. Artificial Intelligence, William Kaufmann, 1981, pp. 674−679.
11. R. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision, Cambridge Univ. Press, 2003.
12. A. Rényi, "On Measures of Entropy and Information," Proc. 4th Berkeley Symp. Mathematics, Statistics, and Probability, vol. 1, 1960, pp. 547–561.
13. L.M. Millward, A. Morgan, and M.P. Kelly, Prevention and Reduction of Accidental Injury in Children and Older People, Health Development Agency, UK Nat'l Health Service, 2003.
14. G.R. Hayes and G.D. Abowd, "Tensions in Designing Capture Technologies for an Evidence-Based Care Community," Proc. SIGCHI Conf. Human Factors in Computing Systems, ACM Press, 2006, pp. 937−946.
15. J.A. Kientz and G.D. Abowd, "KidCam: Toward an Effective Technology for the Capture of Children's Moments of Interest," Proc. Pervasive 2009, LNCS 5538, Springer, 2009, pp. 115−132.
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