I am starting this discussion to bring to together all of the different types of software people are using to process photos collected with their drones and also what they are using it for and what limitations they are finding.
I am currently using the following software:
Agisoft Photoscan Pro
-The data I am running through it was not collected for photogrammetry so I am having some difficulties
-Some images are collected in winter with on the ground making it harder for photoscan to find matching points
-Some images do not have enough overlap or not good enough quality
-Images over forested landscapes sometimes have problems finding matching points
I have using this for quick stitching of images with too little overlap for Photoscan.
I have found it does not work well for long linear set of images
I use google earth to find coordinates for ground control points or georeferencing.
Is an open source GIS software that I use for georeferencing stitched or single images and creating data from the images
I also do a lot of work with LiDAR data and as such am very interested in classifying the point cloud that I can create with Photoscan. The new version has a tool for classifying ground points and then allowing you manually sort the rest. But I am also interested in using the one thing the advantage that photogrammetrically derived points clouds have over raw Lidar data and that is point cloud colours. I am interested in creating a work flow to classify orthos created into feature types (as can already be done) and then assigning these feature type to the point cloud that is also created.
There's another video showing a workflow for 3D engine meshes that uses this new tool:
You don't have to reduce the point cloud density that much as in this video, but of course with many more points the poisson runs slower. It's using solverDivide 7 and depth 10 in this case. You can increase them to make the cloud finer. The final mesh does not use the original points I think, so they're relocated along the calculated mesh. You do need point normals. You should check for non-manifold points later, it seems to leave some points/edges that are non-manifold sometimes.
In my end results you see the blobbyness as well. That's because that vegetation got only a very small number of points, so it's building a 'guess' hull around those points. If you want sharper edges, more points are needed.
If you want things to look better, I'd go into cloudcompare and work on the points there before poisson. You could try resampling around building edges to increase point density there.
I am using VisualSFM to process 27 images taken by a fixed wing UAV(for my final year thesis-Undergraduate study).I downloaded the data from Trimble UASMaster Sample datasets. The 3D point clouds have large gaps and holes in many places.Other software like LPS,Agisoft and PIX4D have generated satisfactory results.I have tried contacting different experts and data providers but i am not getting satisfactory response which can solve this issue. Please kindly suggest me how to deal with this problem.
Hi, there's a new online service for image processing:
It seems costless.