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How would you train a model which detect a patient have fallen down?
Do you train with a lot of images of people falling down (if you don't mind me asking) ? I think having some kind of sensor beside the bed will do well than neural net, although you have to add a lot of sensor (which I think will cost a lot).
Since I think image distribution (old people falling down) of people falling which you want to use is hard to gather , data argumentation is the only way to goes. But how realistic is those data argumentation until it become bias? Oops look like I run off my mouth (finger in this case) here.
Oh you solve it with people detector. I think it will work something like this
1) Detect people
2) Detect when people change position in the image
3) Check if people in the new image is flat on the ground.
Asking an actors to fall down in different position look like a fun task :) Don't forget to ask actors to fall down in funny position since people don't fall down flat on the ground.
I am sure you have already thought about it but don't forget the add the distribution of people grabbing part of the bed on the ground or when the sheet fell down upon the people.
I am sure people detector will not work when the bed sheet cover their whole body (since I think the outline have changes). Maybe you could just think of it as irregularity and ignore it.
AleCx042296034dexpert system????! how old are you?!? that is not important
Yeah it is kind of post estimation with other part. He also needed to determine the change in position of a person.
A person on the ground and on the bed will have the same pose (flat) but he only wanted to detect when a person is on the ground.
It may even be a simple neural network which determine whether a person is on a bed.
He already give us a lot of information , it may be rude to ask him for more.