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Using Self-Contradiction to Learn Confidence Measures in Stereo Vision

Mostegel, Christian and Rumpler, Markus and Fraundorfer, Friedrich and Bischof, Horst (2016) Using Self-Contradiction to Learn Confidence Measures in Stereo Vision. In: Proceedings of Computer Vision and Pattern Recognition 2016, pp. 4067-4076. IEEE Xplore. Conference on Computer Vision and Pattern Recognition 2016, 27-30 June 2016, Las Vegas, USA.

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Official URL: http://cvpr2016.thecvf.com/program/news_updates#proceedings


Learned confidence measures gain increasing impor- tance for outlier removal and quality improvement in stereo vision. However, acquiring the necessary training data is typically a tedious and time consuming task that involves manual interaction, active sensing devices and/or synthetic scenes. To overcome this problem, we propose a new, flexi- ble, and scalable way for generating training data that only requires a set of stereo images as input. The key idea of our approach is to use different view points for reason- ing about contradictions and consistencies between multi- ple depth maps generated with the same stereo algorithm. This enables us to generate a huge amount of training data in a fully automated manner. Among other experiments, we demonstrate the potential of our approach by boost- ing the performance of three learned confidence measures on the KITTI2012 dataset by simply training them on a vast amount of automatically generated training data rather than a limited amount of laser ground truth data.

Item URL in elib:https://elib.dlr.de/105149/
Document Type:Conference or Workshop Item (Poster)
Title:Using Self-Contradiction to Learn Confidence Measures in Stereo Vision
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Mostegel, Christianmostegel (at) icg.tugraz.atUNSPECIFIED
Rumpler, Markusrumpler (at) icg.tugraz.atUNSPECIFIED
Fraundorfer, Friedrichfriedrich.fraundorfer (at) dlr.deUNSPECIFIED
Bischof, Horstbischof (at) icg.tu-graz.ac.atUNSPECIFIED
Journal or Publication Title:Proceedings of Computer Vision and Pattern Recognition 2016
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:No
Page Range:pp. 4067-4076
Publisher:IEEE Xplore
Keywords:Confidence Measures, Stereo Vision
Event Title:Conference on Computer Vision and Pattern Recognition 2016
Event Location:Las Vegas, USA
Event Type:international Conference
Event Dates:27-30 June 2016
Organizer:IEEE Computer Society and the Computer Vision Foundation (CVF)
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Traffic Management (old)
DLR - Research area:Transport
DLR - Program:V VM - Verkehrsmanagement
DLR - Research theme (Project):V - Vabene++ (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Photogrammetry and Image Analysis
Deposited On:20 Jul 2016 10:35
Last Modified:31 Jul 2019 20:02

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