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Experiments with Computer Vision Methods for Fall Zhong Zhang, Eric Becker, Roman Arora, and Vassilis Athitsos
 

Summary: Experiments with Computer Vision Methods for Fall
Detection
Zhong Zhang, Eric Becker, Roman Arora, and Vassilis Athitsos
Computer Science and Engineering Department
University of Texas at Arlington
Arlington, Texas, USA
ABSTRACT
The goal of a fall detection system is to automatically detect cases
where a human falls and may have been injured. A natural ap-
plication of such a system is in home monitoring of patients and
elderly persons, so as to automatically alert relatives and/or author-
ities in case of an injury caused by a fall. This paper describes
experiments with three computer vision methods for fall detection
in a simulated home environment. The first method makes a deci-
sion based on a single frame, simply based on the vertical position
of the image centroid of the person. The second method makes a
threshold-based decision based on the last few frames, by consider-
ing the number of frames during which the person has been falling,
the magnitude (in pixels) of the fall, and the maximum velocity
of the fall. The third method is a statistical method that makes a

  

Source: Athitsos, Vassilis - Department of Computer Science and Engineering, University of Texas at Arlington

 

Collections: Computer Technologies and Information Sciences