Authors: Michael Starks
Anyone shooting 3D is immediately confronted with the problem of stereo camera geometry—how to align the cameras for best results. This looks like it should be the easiest part of the entire project but in fact it’s by far the hardest. Just aligning the cams perfectly in all 3 axes and locking them down is tough and keeping them aligned when changing interaxial, convergence or zoom is extremely hard. There is very little in the way of comprehensive reviews of this subject in the literature. Some may be surprised to learn that these problems are not new, nor are they unique to 3D video and photography. In addition to attention from stereographers for over 150 years, they have been the subject of intensive research in the fields of photogrammetry going back well over 100 years, and more recently in computer vision. Every book in these arenas has extensive discussions on multiple camera geometry and essentially the entire texts revolve around the problems of camera registration and image rectification for human viewing and/or computer image understanding. Algorithmic transforms for producing rectified images from single moving cameras, polydioptric (plenoptic or multiple image single lens cameras) or multiple cameras take up large sections of these books and thousands of papers, which blend into the literatures of robotics, machine vision, artificial intelligence, virtual reality, telepresence and every aspect of 3D imaging. Here I provide a cursory review with a few pertinent references.
Comments: 5 Pages.
[v1] 2015-02-15 21:11:02
Unique-IP document downloads: 30 times
Add your own feedback and questions here:
You are equally welcome to be positive or negative about any paper but please be polite. If you are being critical you must mention at least one specific error, otherwise your comment will be deleted as unhelpful.