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Bachelor thesis "Superpixel Segmentation using Depth Information", including a thorough comparison of several state-of-the-art superpixel algorithms.

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Superpixel Segmentation using Depth Information

Bachelor thesis, David Stutz, RWTH Aachen University, 2014.

Project page: http://davidstutz.de/projects/superpixelsseeds/

A more comprehensive comparison of superpixel algorithms can now be found here: davidstutz.de/project/superpixel-benchmark.

This repository contains the bachelor thesis "Superpixel Segmentation using Depth Information", written at the Computer Vision Group at RWTH Aachen University and supervised by Alexander Hermans and Bastian Leibe.

How to cite this work?

@misc{Stutz:2014,
    author = {David Stutz},
    title = {Superpixel Segmentation using Depth Information},
    month = {September},
    year = {2014},
    institution = {RWTH Aachen University},
    address = {Aachen, Germany},
    howpublished = {http://davidstutz.de/},
}

Also consider citing the corresponding GCPR 2015 paper (which is available here or here):

@incollection{Stutz:2015,
	title = {Superpixel Segmentation: An Evaluation},
	author = {Stutz, David},
	year = {2015},
	isbn = {978-3-319-24946-9},
	booktitle = {Pattern Recognition},
	volume = {9358},
	series = {Lecture Notes in Computer Science},
	editor = {Gall, Juergen and Gehler, Peter and Leibe, Bastian},
	doi = {10.1007/978-3-319-24947-6_46},
	publisher = {Springer International Publishing},
	pages = {555 -- 562},
}

File Index

License

Licenses for source code corresponding to:

D. Stutz. Superpixel Segmentation using Depth Information. Bachelor Thesis, RWTH Aachen University, 2014.

Note that the source code and/or data is based on other projects for which separate licenses apply. See the corresponding subrepositories for details.

Source Code

Copyright (c) 2014-2018 David Stutz, RWTH Aachen University

Please read carefully the following terms and conditions and any accompanying documentation before you download and/or use this software and associated documentation files (the "Software").

The authors hereby grant you a non-exclusive, non-transferable, free of charge right to copy, modify, merge, publish, distribute, and sublicense the Software for the sole purpose of performing non-commercial scientific research, non-commercial education, or non-commercial artistic projects.

Any other use, in particular any use for commercial purposes, is prohibited. This includes, without limitation, incorporation in a commercial product, use in a commercial service, or production of other artefacts for commercial purposes.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

You understand and agree that the authors are under no obligation to provide either maintenance services, update services, notices of latent defects, or corrections of defects with regard to the Software. The authors nevertheless reserve the right to update, modify, or discontinue the Software at any time.

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. You agree to cite the corresponding papers (see above) in documents and papers that report on research using the Software.

Thesis and Slides

Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0); to view a copy of this license, visit https://creativecommons.org/licenses/by-nc/4.0/.

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