文章基本信息

标题：CAMERA-BASED TODDLER FALL DETECTION SYSTEM BY USING KALMAN FILTER
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作者：LOW HAN LEONG ; AINI BT HUSSAIN ; MOHD ASYRAF ZULKIFLEY 等
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2015
卷号：81
期号：2
出版社：Journal of Theoretical and Applied
摘要：Monitoring a toddler is a tedious job, yet a very important one. Fall down is the most common risk that leads to injury during the process of learning to walk. Thus, this paper proposed an algorithm to detect automatically the event of toddler fall down to assist the supervision process by alerting the caretaker if necessary. This system comprises of a background subtraction module to detect region of interest, a tracking module using Kalman filter to track toddler movement and a decision module through decision tree process to determine the toddler state. System performance is evaluated based on three metrics, which are accuracy, sensitivity and specificity. The proposed algorithm works well with a low error performance. Further research should be done to improve the robustness of the system for real life environment implementation.
关键词：Fall Down; Toddler Monitoring; Kalman Filter; Decision Tree Process and Background Subtraction Module