Closed lole-elol closed 1 year ago
DELIVERY PCA
PCA HIST
PCA FFT2
GARDEN PCA
PCA HIST
PCA FFT2
KICKER PCA
PCA HIST
PCA FFT2
PIPES PCA
PCA HIST
PCA FFT2
RELIEF PCA
PCA HIST
PCA FFT2
STATUE PCA
PCA HIST
PCA FFT2
TERRAINS PCA
PCA HIST
PCA FFT2
Sieht gut aus. 1D projection ist leider nicht gut gemug, wir müssen da was besseres machen.
I think the results are pretty good. Especially using Histogram or FFT2 before running the PCA.
I too think more dimensional projections/features could help. We could try using more dimensions from the PCA or combining FFT2 and HIST features into one vector. Maybe the second one would help as they both (HIST, FFT2) perform better in different cases but I don't know how this would affect computation time.
Besides Traveling Salesman we could also try nearest Neighbour to find a path in n dimensional space. I know it's not as exact as traveling salesman but much faster and easier to implement.
I added resorting to the 3D Reconstruction Pipeline in order to benchmark the results.
For this to be easier I combined all resort algorithms in one function. You can now choose between different algorithms with a function argument.
I will run some rough benchmarks using only one of the datasets for now.
@lole-elol tomorrow we can take a closer look at the results and/or run some more benchmarks and tune the algorithms.
Results of the rough benchmarks:
HIST and FFT2 produce okay results but only if the nearest neighbor sorting with 1D results from the PCA is used
Any other settings produce complete garbage results.
@lole-elol @lufixSch is this ready for review?
@lole-elol @lufixSch is this ready for review?
I would like to wait until the meeting tomorrow.
Edit: I read "merge"... Would be nice If you could take a look at it. But I think we will talk about the Algorithms tomorrow.
As far as I'm concerned this can be merged, if you are okay with the structure of the function and it's position in the 3d reconstruction pipeline.
Trying to presort images based on similarity in order to increase point cloud quality. Algorithms: