Increasing depth accuracy with more than two cameras
I'm looking for advice to achieve a high resolution depth map from multiple cameras with OpenCV. My subject is a flower, which has both smooth petal surfaces as well as grass-like hairs protruding from the surface towards the camera. Because these hairs do not have a large surface area and rapidly change their depth, they are difficult to match across the images.
My thought is to use multiple cameras in a grid to both minimize holes in the reconstruction and improve accuracy. For example, with four cameras placed on the vertices of a square, you'd have 6 unique image pairs each with a known baseline.
My questions:
1) Is my subject (a flower) a good fit for stereo matching, or should I use other technology like laser scanners? I'm looking for millimeter accuracy.
2) Is using multiple cameras a good way to improve quality, or should I focus on higher-resolution cameras and more CPU horsepower?
3) Is there anything in OpenCV that would help me stitch together the image pairs? I've seen techniques for doing this with three cameras, but it assumes they are colinear which seems less optimal.
4) Does OpenCV endorse any consulting firms that would help me build this out?
Regards
