WLD: A Wavelet and Learning based Line Descriptor for Line Feature Matching

dc.contributor.authorLange, Manuelen_US
dc.contributor.authorRaisch, Claudioen_US
dc.contributor.authorSchilling, Andreasen_US
dc.contributor.editorKrüger, Jens and Niessner, Matthias and Stückler, Jörgen_US
dc.date.accessioned2020-09-27T18:13:56Z
dc.date.available2020-09-27T18:13:56Z
dc.date.issued2020
dc.description.abstractWe present a machine learning based and wavelet enhanced line feature descriptor for line feature matching. Therefor we trained a neural network to compute a descriptor for a line, given preprocessed information from the image area around the line. In the preprocessing step we utilize wavelets to extract meaningful information from the image for the descriptor. This process is inspired by the human vision system. We used the Unreal Engine 4 and multiple different freely available scenes to create our training data. We conducted the evaluation on ground truth labeled images of our own and from the Middlebury Stereo Dataset. To show the advancement of our method in terms of matching quality, we compare it to the Line Band Descriptor (LBD), to the Deep Learning Based Line Descriptor (DLD), which we used as a starting point for this work, and to the Learnable Line Segment Descriptor for Visual SLAM (LLD). We publish the project on github to support the community: https://github.com/manuellange/WLDen_US
dc.description.sectionheadersSegmentation and Matching
dc.description.seriesinformationVision, Modeling, and Visualization
dc.identifier.doi10.2312/vmv.20201186
dc.identifier.isbn978-3-03868-123-6
dc.identifier.pages39-46
dc.identifier.urihttps://doi.org/10.2312/vmv.20201186
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/vmv20201186
dc.publisherThe Eurographics Associationen_US
dc.subjectComputing methodologies
dc.subjectMatching
dc.subjectComputer vision
dc.subjectNeural networks
dc.subjectMachine learning
dc.titleWLD: A Wavelet and Learning based Line Descriptor for Line Feature Matchingen_US
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