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Andreas Wedel

An Improved Algorithm for TV-L 1 Optical Flow
2009 · Andreas Wedel, Thomas Pock, et al. · Lecture notes in computer science · 438
Anisotropic Huber-L1 Optical Flow
2009 · Manuel Werlberger, Werner Trobin, et al. · British Machine Vision Conference (BMVC) · 365
Object-Oriented Bayesian Networks for Detection of Lane Change Maneuvers
2012 · Dietmar Kasper, Galia Weidl, et al. · IEEE Intelligent Transportation Systems Magazine · 196
Structure- and motion-adaptive regularization for high accuracy optic flow
2009 · Andreas Wedel, Daniel Cremers, et al. · IEEE/CVF International Conference on Computer Vision (ICCV) · 180
Efficient Dense Scene Flow from Sparse or Dense Stereo Data
2008 · Andreas Wedel, Clemens Rabe, et al. · Lecture notes in computer science · 178
Stereoscopic Scene Flow Computation for 3D Motion Understanding
2010 · Andreas Wedel, Thomas Brox, et al. · International Journal of Computer Vision · 167
When will it change the lane? A probabilistic regression approach for rarely occurring events
2015 · Julian Schlechtriemen, Florian Wirthmueller, et al. · IEEE Intelligent Vehicles Symposium · 128
A lane change detection approach using feature ranking with maximized predictive power
2014 · Julian Schlechtriemen, Andreas Wedel, et al. · IEEE Intelligent Vehicles Symposium · 127
B-Spline Modeling of Road Surfaces With an Application to Free-Space Estimation
2009 · A. Wedel, H. Badino, et al. · IEEE Transactions on Intelligent Transportation Systems · 119
Dense, Robust, and Accurate Motion Field Estimation from Stereo Image Sequences in Real-Time
2010 · Clemens Rabe, Thomas Müller, et al. · Lecture notes in computer science · 110
Moving Object Segmentation Using Optical Flow and Depth Information
2009 · Jens Klappstein, Tobi Vaudrey, et al. · Lecture notes in computer science · 87
Stereo Scene Flow for 3D Motion Analysis
2011 · Andreas Wedel, Daniel Cremers · Springer eBooks · 67
Detection and Segmentation of Independently Moving Objects from Dense Scene Flow
2009 · Andreas Wedel, Annemarie Meißner, et al. · Lecture notes in computer science · 65
Duality TV-L1 flow with fundamental matrix prior
2008 · A. Wedel, T. Pock, et al. · International Conference on Image and Vision Computing New Zealand (IVCNZ) · 60
Realtime Depth Estimation and Obstacle Detection from Monocular Video
2006 · Andreas Wedel, Uwe Franke, et al. · Lecture notes in computer science · 51
B-spline modeling of road surfaces for freespace estimation
2008 · Andreas Wedel, Uwe Franke, et al. · IEEE Intelligent Vehicles Symposium · 48
A probabilistic long term prediction approach for highway scenarios
2014 · Julian Schlechtriemen, Andreas Wedel, et al. · IEEE International Conference on Intelligent Transportation Systems (ITSC) · 19
WarpCut – Fast Obstacle Segmentation in Monocular Video
2007 · Andreas Wedel, Thomas Schoenemann, et al. · Lecture notes in computer science · 19
Monocular Video serves RADAR-based Emergency Braking
2007 · Andreas Wedel, Uwe Franke · IEEE Intelligent Vehicles Symposium · 16
Optical Flow Estimation
2011 · Andreas Wedel, Daniel Cremers · Springer eBooks · 14
Evaluation of moving object segmentation comparing 6D-vision and monocular motion constraints
2008 · Tobi Vaudrey, Andreas Wedel, et al. · International Conference on Image and Vision Computing New Zealand (IVCNZ) · 13
A Methodology for Evaluating Illumination Artifact Removal for Corresponding Images
2009 · Tobi Vaudrey, Andreas Wedel, et al. · Lecture notes in computer science · 10
Generalised residual images’ effect on illumination artifact removal for correspondence algorithms
2010 · Tobi Vaudrey, Sandino Morales, et al. · Pattern Recognition · 8
Space-Time Multi-Resolution Banded Graph-Cut for Fast Segmentation
2008 · Tobi Vaudrey, Daniel Gruber, et al. · Lecture notes in computer science · 8
Trajectory Planning for Automated Driving in Intersection Scenarios Using Driver Models
2020 · Oliver Speidel, Maximilian Graf, et al. · International Conference on Robotics and Automation Engineering (ICRAE) · 7
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Works count: 54
Citation count: 2,527
H-index: 18
I10-index: 22
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