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README.md

Depth packet processors and plot functions for Kinect v2 phase unwrapping from log files.

The algorithm is described in the paper Efficient Phase Unwrapping using Kernel Density Estimation, ECCV 2016, Felix Järemo Lawin, Per-Erik Forssén and Hannes Ovrén, see http://www.cvl.isy.liu.se/research/datasets/kinect2-dataset/.

Setup

git clone https://github.com/felja633/kinectv2_decoders.git

Download dataset at www.cvl.isy.liu.se/research/datasets/kinect2-dataset/kinect2_dataset.zip. Unzip kinect2_dataset.zip in the kinectv2_decoders folder

then build the decoders:

cd kinectv2_decoders
mkdir build
cd build
cmake ..
make

Run

We provide three datasets: lecture, kitchen, and library. Choose one as dataset and run the code as:

cd kinectv2_decoders/build
./kinectv2_decoders ../parameters/default_setup.xml dataset
cd ..
python evaluate_decoders.py test parameters/default_setup.xml dataset

To visualize, run code as:

python evaluate_decoders.py vis ../parameters/default_setup.xml dataset

Toggle between frames using the arrow buttons.

Parameters

Parameters are passed in xml-format. At this stage two pipelines are implemented, kde and libfreenect2. Each pipeline that is to be tested should be added in the xml-file. The user can then add and change the parameters freely.

Example:

<pipeline name="kde" setup_name="base">
    <Parameters>
        <kde_sigma_sqr>0.0239282226563</kde_sigma_sqr>
        <unwrapping_likelihood_scale>2.0</unwrapping_likelihood_scale>
        <phase_confidence_scale>3.0</phase_confidence_scale>
        <kde_neigborhood_size>5</kde_neigborhood_size>
        <num_hyps>2</num_hyps>
        <min_depth>500.0</min_depth>
        <max_depth>18750.0</max_depth>
    </Parameters>
</pipeline>

Dependencies

The package requires the hdf5 library to parse Kinect v2 log files.

MacOS X

First Install HDF5 with brew:

brew install homebrew/science/hdf5

Then add the appropriate paths (in bash):

export HDF5=/usr/local/Cellar/hdf5/1.8.17 # Replace with your hdf5 installation full path
export PATH=${HDF5}/bin:${PATH}
export DYLD_LIBRARY_PATH=${HDF5}/lib:${DYLD_LIBRARY_PATH}

Linux

sudo apt-get install libhdf5-dev

About

Code for offline processing and evaluation of depth processing algorithms for the Kinect v2

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