Reddit reviews Multiple View Geometry in Computer Vision
We found 4 Reddit comments about Multiple View Geometry in Computer Vision. Here are the top ones, ranked by their Reddit score.
Cambridge University Press
The most famous textbook on 3D reconstruction is Multiple-View Geometry in Computer Vision, but I'm afraid it's much too complex for you now.
You need to know how matrix and vector operations work, understand projective geometry in 3D (like rays, intersections, planes etc.); learn epipolar geometry and understand the difference between the essential matrix and fundamental matrix; also take a look at some numerical methods and estimation methods (eg homogeneous least squares).
In the meantime, I suggest you take a look at this book: Programming Computer Vision with Python (you can download it for free), there's a chapter explaining the basics of 3D reconstuction with sample code, this can be good motivation for you.
And be patient, this is a pretty complex field, so better learn the basics first!
"We don’t have to worry about strictly lining up the images since they won’t be displayed."
Pretty sure the cameras would have to be calibrated with respect to one another which is not a trivial affair.
This is a good resource for mocap / reconstruction:
http://www.amazon.com/Multiple-View-Geometry-Computer-Vision/dp/0521540518
Yep, you've got it! Pick up Multiple View Geometry if you really want to get your hands dirty.
Came at this from the opposite direction - needed to write projection calibration algorithms; this incredibly useful book supplied the linalg algorithms: https://www.amazon.co.uk/Multiple-Geometry-Computer-Vision-Second/dp/0521540518/