This is a release of GPU Scanalyze 64bit for Windows 7 (I am stressing that you should have a 64bit Windows 7 OS and have downloaded the 64bit CUDA Toolkit Version 4 or above). Scanalyze is an application for registering meshes using ICP and has been developed at Stanford University under the supervision of Prof. Marc Levoy. The bottleneck of ICP is finding the pairs that are close with each other between the two meshes.
I am using for the time being (and I think will be using) Lawrence Cayton RBC in GPU for finding these pairs.
Download it in your CUDA enabled Windows 7 64bit PC and use it either as a hobby or professionally (yes it is a Professional registration tool since it is in 64bit) for small to very large datasets. I have tested it registering two 25 Millions of Points datasets and it works (the larger the mesh, the less sampling rate you should use).
Use : Unzip (rather unrar :-) the application and go into ScanalyzeGPU64bit/scanalyze and double click scanalyze.bat.
Important note : [i]In order to run the ICP process of GPUScanalyze you should have sufficient GPU memory. For this reason I have put at the lower right end two meters of the form CPU:xxx / GPU:xxx
The first meter indicates how much memory ScanalyzeGPU occupies on the CPU side (Host side) and the GPU meter tells you how much remaining GPU memory you have for CUDA purposes. If the GPU meter is very low ICP might not run, ICP is not performed in this case.
Here is a video of how to register meshes :
The above registration is just a demo, it needed more culling in order to be precise.
Also since Lawrence RBC is extremely fast even on a million point data set sampling, use the maximum in iterations (20).
Just to show an example I have reconstructed Stanford’s dragon.
First comes the registration step where the scans provided by Stanford are aligned using GPUScanalyze :
This session involved the registration of 50+ range views and I did not find any trouble, thus the process is error proof.
Here are the data (ply file) of the aligned data set : Dragon aligned
Next I have used Poisson surface reconstruction on the aligned data set and got this very smooth result :
Here are the data (ply file) of the reconstructed 3D object : Dragon reconstructed
If you use it for commercial, educational purposes please mention that Scanalyze was created in Stanford University and if you like my name.
Scanalyze GPU Download link : ScanalyzeGPU64bit