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Vision-based fall detection is a challenging problem in pattern recognition. This paper introduces an approach to detect a fall as well as its type in color video sequences. Accumulative computation is used to segment the color videos for the sake of robustly detecting humans. The regions of interest of the segmented humans are examined through calculating geometrical and kinematic features. The fall indicators used as well as their fuzzy model are explained in detail. The fuzzy model has been tested for a wide number of static and dynamic falls.
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