This repository contains the source code corresponding to the method presented in the paper:
- Confidence driven TGV fusion, V. Ntouskos, F. Pirri, arXiv: arXiv:1603.09302, 2016.
###Contact:
Valsamis Ntouskos [email protected], http://www.diag.uniroma1.it/~ntouskos;
ALCOR Lab [email protected] http://www.diag.uniroma1.it/~alcor,
###Instructions###
To run the demo you need to download the KITTI 2012 multiview dataset (data, calibration files, and multi-view extension) from here.
The disparity maps for all the stereo-pairs of the dataset, computed based on the method presented in the paper "Confidence driven TGV fusion", J. Zbontar and Y. LeCun, CVPR, 2015, are available for download from here.
###Quickstart###
-
Compile the CUDA kernels located in the
./cuda
folder. Under Windows you can use the provided Makefile:nmake -f Makefile.win all
; -
Modify the path variables
basedir
andw_path
in the demo scriptdemo_kitti
. -
Execute the demo script:
demo_kitti
.
##Synthetic Datasets ###Instructions### You can run the scripts that process the synthetic datasets used in the paper. These datasets are available for download from here.
###Quickstart###
-
Compile the CUDA kernels located in the
./cuda
folder. Under Windows you can use the provided Makefile:nmake -f Makefile.win all
; -
Modify the path variables
basedir
andw_path
in the demo scriptsproc_synth_data_objects
andproc_synth_data_urban
. -
Execute the script:
proc_synth_data_objects
orproc_synth_data_urban
. -
Use script
showSurf
to visualize the surfaces corresponding to the fused depth images.
You need the CUDA Toolkit (version 6 or later) and a compatible compiler in order to compile the CUDA kernels.