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Issue No. 01 - January-March (2011 vol. 10)
ISSN: 1536-1268
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

H. Na, S. Qin and D. K. Wright, "Detecting Fall Risk Factors for Toddlers," in IEEE Pervasive Computing, vol. 10, no. , pp. 82-89, 2010.
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