This forum is disabled, please visit https://forum.opencv.org
 | 1 | initial version |
I have a partial answer:
1) You may have two different applications of stereo matching here. You may need to filter the input images to: enhance the lower frequency smooth surfaces and solve for smooth, wide changes (petals), and then enhance the images for high-frequency narrow items pointing toward the camera, and solve that (stamens/pistils), then merge the results intelligently, rejecting the parts that are not of interest.
The stereo algorithms are not ideal for detecting depth of narrow things pointed right at the camera, but they can resolve surfaces that are more parallel to the camera fairly well. To image the narrow stems, you may need to have depth cameras imaging the scene more obliquely.
2) Multiple cameras are an excellent way to fill in parts of the solution hidden by tall objects pointing toward the camera. I've used this technique to good results. One needs to consider point cloud vs. depth map vs. modeled shape merging and filtering though, to solve this problem, and there are a lot of choices there.
I won't comment on stitching since that is not my area of expertise.
