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Dataset on underwater change detection

 
: Radolko, Martin; Lukas, Uwe von; Farhadifard, Fahimeh

:
Postprint urn:nbn:de:0011-n-4424747 (10 MByte PDF)
MD5 Fingerprint: 7f2376c775655b3e096bf2cc1c536c03
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Created on: 20.9.2017


Institute of Electrical and Electronics Engineers -IEEE-; Marine Technology Society -MTS-; IEEE Oceanic Engineering Society:
MTS/IEEE Monterey OCEANS 2016 : 19-23 September 2016, Monterey
Piscataway, NJ: IEEE, 2016
ISBN: 978-1-5090-1527-6 (Print)
ISBN: 978-1-5090-1537-5
8 pp.
Oceans Conference and Exhibition (OCEANS) <2016, Monterey/Calif.>
English
Conference Paper, Electronic Publication
Fraunhofer IGD ()
evaluation of segmentation; image segmentation; Guiding Theme: Visual Computing as a Service; Research Area: Computer vision (CV)

Abstract
The detection of moving objects in a scene is a well researched but depending on the concrete research still often a challenging computer vision task. Usually it is the first step in a whole pipeline and all following algorithms (tracking, classification etc.) are dependent on the accuracy of the detection. Hence, a good pixel-precise segmentation of the objects of interest is mandatory for many applications. However, the underwater environment has mostly been neglected so far and there exists no common dataset to evaluate different algorithms under the harsh underwater conditions and therefore a comprehensive evaluation is impossible. In this paper, we present an underwater change detection dataset consisting of five videos and hundreds of handsegmented ground truth images as well as a survey of different underwater image enhancement techniques and their impact on segmentation algorithms.

: http://publica.fraunhofer.de/documents/N-442474.html