Abstract:
This paper proposes an computing analysis on
human geometric shape features to detect a fall
behavior. The system mainly computes the changes
on human orientation (torso angle) and centroid
height via the human skeleton joints extracted by
Kinect sensor. The system computes and tracks the
spatial changes of these human orientation and
centroid height and distinguishs a fall behavior
among other daily activities by using a thresholding
algorithm. The main objective of this computation is
to minize the computational time and to increase the
true alarms in developing a fall detection. The system
works the feature extraction on our collected fall
detection dataset containing the fall data along with
daily activities such as sitting down, lying, combing.
Standing, etc., are collected by Microsoft Kinect
sensor.
