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Daniel Kondermann
Daniel Kondermann
Quality Match GmbH
Zweryfikowany adres z quality-match.com - Strona główna
Tytuł
Cytowane przez
Cytowane przez
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A dataset and evaluation methodology for depth estimation on 4D light fields
K Honauer, O Johannsen, D Kondermann, B Goldluecke
Computer Vision–ACCV 2016: 13th Asian Conference on Computer Vision, Taipei …, 2017
5712017
Horn-schunck optical flow with a multi-scale strategy
E Meinhardt-Llopis, J Sánchez
Image Processing on line, 2013
1722013
Ensemble learning for confidence measures in stereo vision
R Haeusler, R Nair, D Kondermann
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2013
1442013
The hci benchmark suite: Stereo and flow ground truth with uncertainties for urban autonomous driving
D Kondermann, R Nair, K Honauer, K Krispin, J Andrulis, A Brock, ...
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016
1372016
Blood vessel classification into arteries and veins in retinal images
C Kondermann, D Kondermann, M Yan
Medical Imaging 2007: Image Processing 6512, 1401-1409, 2007
1342007
Can masses of non-experts train highly accurate image classifiers? A crowdsourcing approach to instrument segmentation in laparoscopic images
L Maier-Hein, S Mersmann, D Kondermann, S Bodenstedt, A Sanchez, ...
Medical Image Computing and Computer-Assisted Intervention–MICCAI 2014: 17th …, 2014
972014
A survey on time-of-flight stereo fusion
R Nair, K Ruhl, F Lenzen, S Meister, H Schäfer, CS Garbe, M Eisemann, ...
Time-of-Flight and Depth Imaging. Sensors, Algorithms, and Applications …, 2013
962013
When can we use kinectfusion for ground truth acquisition
S Meister, S Izadi, P Kohli, M Hämmerle, C Rother, D Kondermann
Proc. Workshop on Color-Depth Camera Fusion in Robotics 2, 3, 2012
922012
Outdoor stereo camera system for the generation of real-world benchmark data sets
S Meister, B Jähne, D Kondermann
Optical Engineering 51 (2), 021107-021107, 2012
872012
A statistical confidence measure for optical flows
C Kondermann, R Mester, C Garbe
Computer Vision–ECCV 2008: 10th European Conference on Computer Vision …, 2008
702008
Crowdsourcing for reference correspondence generation in endoscopic images
L Maier-Hein, S Mersmann, D Kondermann, C Stock, HG Kenngott, ...
Medical Image Computing and Computer-Assisted Intervention–MICCAI 2014: 17th …, 2014
512014
A state of the art report on kinect sensor setups in computer vision
K Berger, S Meister, R Nair, D Kondermann
Time-of-Flight and Depth Imaging. Sensors, Algorithms, and Applications …, 2013
502013
An adaptive confidence measure for optical flows based on linear subspace projections
C Kondermann, D Kondermann, B Jähne, C Garbe
Pattern Recognition: 29th DAGM Symposium, Heidelberg, Germany, September 12 …, 2007
492007
Real versus realistically rendered scenes for optical flow evaluation
S Meister, D Kondermann
2011 14th ITG Conference on Electronic Media Technology, 1-6, 2011
472011
High accuracy tof and stereo sensor fusion at interactive rates
R Nair, F Lenzen, S Meister, H Schäfer, C Garbe, D Kondermann
Computer Vision–ECCV 2012. Workshops and Demonstrations: Florence, Italy …, 2012
442012
Ground truth design principles: an overview
D Kondermann
Proceedings of the International Workshop on Video and Image Ground Truth in …, 2013
332013
Simulation of Time-of-Flight Sensors using Global Illumination.
S Meister, R Nair, D Kondermann
VMV, 33-40, 2013
302013
Crowdtruth validation: a new paradigm for validating algorithms that rely on image correspondences
L Maier-Hein, D Kondermann, T Roß, S Mersmann, E Heim, S Bodenstedt, ...
International journal of computer assisted radiology and surgery 10, 1201-1212, 2015
292015
Stereo ground truth with error bars
D Kondermann, R Nair, S Meister, W Mischler, B Güssefeld, K Honauer, ...
Computer Vision--ACCV 2014: 12th Asian Conference on Computer Vision …, 2015
292015
On performance analysis of optical flow algorithms
D Kondermann, S Abraham, G Brostow, W Förstner, S Gehrig, A Imiya, ...
Outdoor and Large-Scale Real-World Scene Analysis: 15th International …, 2012
272012
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