/bachelor-thesis-superpixels

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

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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/.