Is it not a little surprising that the patch just has to be roughly where the person's belly is? You'd think the NN identifies people by finding a face and maybe limbs. Or a head-and-shoulders. But maybe it doesn't.
The neural network isn't looking for a head, limbs etc... It's just looking for overall patterns.
The soft used in the article is Yolo and I work a lot with it, and the results depends A LOT on the data you used for training. Some datasets will detect a gorilla as an human, some won't. Some even will detect two upside down fingers as a human.
So if you want your NN to not detect gorillas as a human, you have to include pictures containing gorillas where they are not labelled as humans.
It makes a certain sort of sense - if a person's torso isn't connected to their legs, it's not very person shaped, is it.
I'd agree it's surprising, just that thinking about it you can see where it goes wrong. I imagine combining this with some kind of makeup to change the contours of one's face would work wonders.
> if a person's torso isn't connected to their legs, it's not very person shaped, is it.
I suppose it really depends on the training set. In some sense the set can be misleading. For instance if I have a load of pictures of people sitting by a table with their legs visible, that model might actually require a gap between your torso and your legs.
That's true. In fact in the video, the man's lower legs are obscured by the chair and this poses little problem for the system. However, I would say that if this was all that were required, they would have used a blank square.
Instead, they provide cues that mess with the system's sense of scale, by having almost like a window into another, smaller scene, with vague, human-like images that the network presumably recognises as faces.
A group of tiny faces on the top of a single set of legs very much does not look like a human.
What would happen to a gorilla wearing the patch?