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Blockwise Multi-Order Feature Regression for Real-Time Path Tracing Reconstruction

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# Blockwise Multi-Order Feature Regression for Real-Time Path Tracing Reconstruction

This is the code used in the paper:

"Blockwise Multi-Order Feature Regression for Real-Time Path Tracing Reconstruction".

by Koskela M., Immonen K., Mäkitalo M., Foi A., Viitanen T., Jääskeläinen P., 
Kultala H., and Takala J.

Virtual reality and Graphics Architectures (VGA) group, Tampere University, http://www.tuni.fi/vga/

# Datasets

The dataset to run the code is around 19GB because it contain 60 frames
animations of 7 scenes with references and feature buffers all in
single-precision .exr format.

The datasets can be found here: http://www.tuni.fi/vga/bmfr

# Building

Make sure that you have the dataset's "inputs" folder at the location defined
by `INPUT_DATA_PATH`, which can be found in `opencl/bmfr.cpp`

You need to rebuild the project if you change the files in the location without
changing the `INPUT_DATA_PATH`. It changes the `camera_matrices.h` and the
makefile/project does not check its modification date because the path to it is
defined in the `bmfr.cpp` file.

## Linux

Install OpenCL driver and OpenImageIO library.

`make && ./bmfr` in `opencl` folder should build and run the code.

## Windows

Building and running the `bmfr.sln` with Visual Studio 2017 should work out of
the box.

# Notes

Defines in the `bmfr.cpp` file can be used to:
 * Edit some of the BMFR algorithm's parameters
 * Run the code with different inputs
 * Change some of the optimizations for finding the fastest runtime on your
   target hardware

bmfr

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