Earlier quoted context omitted.
Super cool course! Thanks for the link! Do you know what are the most precise programmable RGB-D cameras a non-professional can buy? I was trying to extract 3D information just from a single camera via 3D convolutions and RNNs (for a self-driving car project) and would like to play with real 3D a bit as well.
(I wrote the original article) I've been playing around with a few and I'd recommend the Orbbec Astra and the Intel RealSense (the new D435 is what I've been using) as decent but cheap cameras if you want to get started! The Asus Xtion PRO LIVE is also quite good but since it's been discontinued it's pretty hard to find. The Stereolabs ZED relies on stereo vision but produces a similar output as traditional RGB-D cam…
Beyond the pixel plane: sensing and learning in 3D
11–16 of 16 posts
Re: Beyond the pixel plane: sensing and learning in 3D
#12Earlier quoted context omitted.
(I wrote the original article) I've been playing around with a few and I'd recommend the Orbbec Astra and the Intel RealSense (the new D435 is what I've been using) as decent but cheap cameras if you want to get started! The Asus Xtion PRO LIVE is also quite good but since it's been discontinued it's pretty hard to find. The Stereolabs ZED relies on stereo vision but produces a similar output as traditional RGB-D cam…
Any idea if the iPhone X surfaces RGBD from the TrueDepth camera?
Re: Beyond the pixel plane: sensing and learning in 3D
#13Earlier quoted context omitted.
Super cool course! Thanks for the link! Do you know what are the most precise programmable RGB-D cameras a non-professional can buy? I was trying to extract 3D information just from a single camera via 3D convolutions and RNNs (for a self-driving car project) and would like to play with real 3D a bit as well.
(I wrote the original article) I've been playing around with a few and I'd recommend the Orbbec Astra and the Intel RealSense (the new D435 is what I've been using) as decent but cheap cameras if you want to get started! The Asus Xtion PRO LIVE is also quite good but since it's been discontinued it's pretty hard to find. The Stereolabs ZED relies on stereo vision but produces a similar output as traditional RGB-D cam…
You promise some directions for fruitful research. It is a bit light on that. Maybe it's nice to expand on that topic a bit more.
Re: Beyond the pixel plane: sensing and learning in 3D
#14This is a great overview. Also checkout CS 468 from Stanford, http://graphics.stanford.edu/courses/cs468-17-spring/ "Machine Learning for 3D Data" Also, if you want to work on this stuff full time- https://news.ycombinator.com/item?id=17649726
Super cool course! Thanks for the link! Do you know what are the most precise programmable RGB-D cameras a non-professional can buy? I was trying to extract 3D information just from a single camera via 3D convolutions and RNNs (for a self-driving car project) and would like to play with real 3D a bit as well.
Re: Beyond the pixel plane: sensing and learning in 3D
#15Earlier quoted context omitted.
(I wrote the original article) I've been playing around with a few and I'd recommend the Orbbec Astra and the Intel RealSense (the new D435 is what I've been using) as decent but cheap cameras if you want to get started! The Asus Xtion PRO LIVE is also quite good but since it's been discontinued it's pretty hard to find. The Stereolabs ZED relies on stereo vision but produces a similar output as traditional RGB-D cam…
Any idea if the iPhone X surfaces RGBD from the TrueDepth camera?
Re: Beyond the pixel plane: sensing and learning in 3D
#16What about pose estimation? e.g. Given a well defined coordinate system, like the origin is the nose on a face, determine the pose of the face. Is this still best done with classic optimization formulations like ransac/ICP and a supplied model, or have these been bested by learned models somehow?
Don't think it's exactly what you're talking about (I'm sure there are other works much closer to what you have in mind, just can't recall off the top of my head) — but you might find PoseNet ( https://www.cv-foundation.org/openaccess/content_iccv_2015/p... ) interesting. Not explicitly 3D, but estimates where in a large-scale scene a picture was taken using an end-to-end convolutional network. With that said, I thin…
[1] Web-browser demo: https://storage.googleapis.com/tfjs-models/demos/posenet/cam... [2] Github: https://github.com/tensorflow/tfjs-models/tree/master/posene...