Fall Detection
Zhong
Zhang and Vassilis Athitsos
Abstract
The goal of a fall detection
system is to automatically detect cases where a human falls and may have been
injured. A natural application of such a system is in home monitoring of
patients and elderly persons, so as to automatically alert relatives and/or
authorities in case of an injury caused by a fall. We propose a statistical
method based on Kinect that makes a decision based on the last few frames, by
considering the number of frames during which the person has been falling, the
magnitude of the fall, the maximum velocity of the fall and the rate of
decrease frame-by-frame during the fall. Since the range of depth sensor is
from 0:5m to 4m, one Kinect is not enough to cover the whole space. We set two
Kinects in our home environment. Our user independent and camera independent
test shows that our method is applicable in real life.
Experimental Scenario
The experiment data for this
paper come from experiments run in the Heracleia
Human Centered Computing Laboratory at the University of Texas at Arlington. In
this lab, a simulated apartment has been set up. Two Kinects were set up at two
corners of the apartment, and were set to monitor the apartment. The reason of
setting two Kinects is that the range of depth sensor is from 0:5m to 4m, which
means one Kinect is not enough to cover the whole
apartment. The first row in the following figure is view 1 and the second row
is view 2. The left side is depth map while the right side is color map.
Experimental Data
Six subjects do several
actions in two scenes separately. Download the data set from the following
links.
As for how to read the
depth map, please use the following matlab file.
These actions include real falls and other fall-like actions, such as picking up a coin from floor, sitting down on the floor, tying shoelaces and etc. There are 10400 frames and 12 real falls in scene 1 while 21214 frames and 14 real falls in scene 2. The following table shows fall-like actions in our experiment.
|
Pf |
Ts |
Sb |
Sif |
Pd |
Jb |
Sf |
|
23 |
10 |
9 |
12 |
5 |
1 |
1 |
In the above table, pf means picking up something from floor, ts means tying shoelaces, sb
means sleeping down on the bed, sif means sitting on
the floor, pd means opening the lower drawer, which
is very close to the floor, jb means jumping on to
the floor and sf means sleeping down on the floor.
The following figures show a
fall process.
A fall process
We also annotate the start and
end frame for every fall process.
In the annotation file, the format is like: Alexis view1 202 215.Alexis is the user name. view1 means scene 1. 202 is the start frame and 215 is the end frame.
The following figures show a
typical fall-like action, which is sitting on the floor.
Sitting on the floor