3 ms·

I don't think this is all that amazing. Human fingers only have a very narrow range of motion in a single direction. When the 2D profile of the hand changes,

I don't think this is all that amazing. Human fingers only have a very narrow range of motion in a single direction. When the 2D profile of the hand changes, the set of finger movements to arrive at that profile is fairly predictable.

regularfry 9y ago
As someone who's been keeping tabs on the field for the past 20 years since briefly bouncing through it at university, you're dead wrong. It's one of those things that sounds easy, and... just isn't. The shots of predicting the partially occluded pose are a bit special, too.
ska 9y ago
You think so in the first 5 minutes of thinking about it, then you try it, and then you realize why lots of smart people have struggled with improving this in the last decades. Compute vision is full of problems that turn out to be a lot harder than they look. Part of the reason is that our intuition about this is skewed by having access to a very good vision processing unit that we can't reproduce :)
KineticLensman 9y ago
> "Human fingers only have a very narrow range of motion in a single direction" Each finger has three joints that can bend in and a little bit back. Each finger can move from side to side. There is a small amount of rotation around the base of the finger. The thumb has three joints, the bottom of which is opposable to create a gripping hand. The entire hand can bend, yaw and rotate with respect to the arm, and there is further flexibility in the bones of the palm. If you doubt how complicated the hand is, download a free 3D figure posing system like Daz Studio [1], instantiate a figure, and then try to make a hand grip a small object, or gesture (e.g. v-sign, 'ok', hitchhiking, vulcan greeting). [1] https://www.daz3d.com/ https://www.daz3d.com/
- jordache 9y ago
  A lot of the variables you listed is not relevant. The solution linked here is only deriving the 3d positions of the fingers, none of the other nuances that can be expressed by the hand's muscular and skeletal system.
iaw 9y ago
Have you tried to implement visual algorithms? Especially those prior to the prevalence of GPU-based neural networks? Even just ten years ago it was non-trivial to predict the shape of a room from a single 2d RGB image.
anjc 9y ago
Try it and see. You're right that skeletal constraints help.

regularfry 9y ago

As someone who's been keeping tabs on the field for the past 20 years since briefly bouncing through it at university, you're dead wrong. It's one of those things that sounds easy, and... just isn't. The shots of predicting the partially occluded pose are a bit special, too.

ska 9y ago

You think so in the first 5 minutes of thinking about it, then you try it, and then you realize why lots of smart people have struggled with improving this in the last decades. Compute vision is full of problems that turn out to be a lot harder than they look. Part of the reason is that our intuition about this is skewed by having access to a very good vision processing unit that we can't reproduce :)

KineticLensman 9y ago

> "Human fingers only have a very narrow range of motion in a single direction" Each finger has three joints that can bend in and a little bit back. Each finger can move from side to side. There is a small amount of rotation around the base of the finger. The thumb has three joints, the bottom of which is opposable to create a gripping hand. The entire hand can bend, yaw and rotate with respect to the arm, and there is further flexibility in the bones of the palm. If you doubt how complicated the hand is, download a free 3D figure posing system like Daz Studio [1], instantiate a figure, and then try to make a hand grip a small object, or gesture (e.g. v-sign, 'ok', hitchhiking, vulcan greeting). [1] https://www.daz3d.com/ https://www.daz3d.com/

jordache 9y ago
A lot of the variables you listed is not relevant. The solution linked here is only deriving the 3d positions of the fingers, none of the other nuances that can be expressed by the hand's muscular and skeletal system.

iaw 9y ago

Have you tried to implement visual algorithms? Especially those prior to the prevalence of GPU-based neural networks? Even just ten years ago it was non-trivial to predict the shape of a room from a single 2d RGB image.

anjc 9y ago

Try it and see. You're right that skeletal constraints help.