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confidence-fusion

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Confidence driven image fusion based on TGV regularization

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# Confidence driven TGV fusion

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 <ntouskos@diag.uniroma1.it>, [http://www.diag.uniroma1.it/~ntouskos](http://www.diag.uniroma1.it/~ntouskos);

ALCOR Lab <alcor@diag.uniroma1.it> [http://www.diag.uniroma1.it/~alcor](http://www.diag.uniroma1.it/~alcor),

## KITTI 2012##
###Instructions###

To run the demo you need to download the KITTI 2012 multiview dataset (data, calibration files, and multi-view extension) from [here](http://www.cvlibs.net/datasets/kitti/eval_stereo_flow.php?benchmark=stereo).

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](http://www.dis.uniroma1.it/~alcor/site/datasets/kitti_2012_mv_cm-cnn.zip).

###Quickstart###
1. Compile the CUDA kernels located in the `./cuda` folder. Under Windows you can use the provided Makefile: `nmake -f Makefile.win all`;

1. Modify the path variables `basedir` and `w_path` in the demo script `demo_kitti`.

1. 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](http://www.dis.uniroma1.it/~alcor/site/datasets/fusion_synthetic_data.zip).

###Quickstart###
1. Compile the CUDA kernels located in the `./cuda` folder. Under Windows you can use the provided Makefile: `nmake -f Makefile.win all`;

1. Modify the path variables `basedir` and `w_path` in the demo scripts `proc_synth_data_objects` and `proc_synth_data_urban`.

1. Execute the script:
`proc_synth_data_objects` or `proc_synth_data_urban`.

1. Use script `showSurf` to visualize the surfaces corresponding to the fused depth images.

## External dependencies

You need the CUDA Toolkit (version 6 or later) and a compatible compiler in order to compile the CUDA kernels.

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