Torben Fetzer

According to our database1, Torben Fetzer authored at least 11 papers between 2017 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2023
On Sinusoidal Structured Light Reconstruction - An Entire Pipeline with Improvements in Accuracy, Stability, Robustness and Speed.
PhD thesis, 2023

2022
INV-Flow2PoseNet: Light-Resistant Rigid Object Pose from Optical Flow of RGB-D Images Using Images, Normals and Vertices.
Sensors, 2022

ZebraPose: Coarse to Fine Surface Encoding for 6DoF Object Pose Estimation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Fast Projector-Driven Structured Light Matching in Sub-pixel Accuracy Using Bilinear Interpolation Assumption.
Proceedings of the Computer Analysis of Images and Patterns, 2021

Joint Global ICP for Improved Automatic Alignment of Full Turn Object Scans.
Proceedings of the Computer Analysis of Images and Patterns, 2021

Simultaneous Bi-directional Structured Light Encoding for Practical Uncalibrated Profilometry.
Proceedings of the Computer Analysis of Images and Patterns, 2021

2020
Stable Intrinsic Auto-Calibration from Fundamental Matrices of Devices with Uncorrelated Camera Parameters.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

Iterative Color Equalization for Increased Applicability of Structured Light Reconstruction.
Proceedings of the 15th International Joint Conference on Computer Vision, 2020

2019
Robust Auto-Calibration for Practical Scanning Setups from Epipolar and Trifocal Relations.
Proceedings of the 16th International Conference on Machine Vision Applications, 2019

2017
Accurate 3D Reconstruction of Dynamic Scenes from Monocular Image Sequences with Severe Occlusions.
Proceedings of the 2017 IEEE Winter Conference on Applications of Computer Vision, 2017

Introduction to Coherent Depth Fields for Dense Monocular Surface Recovery.
Proceedings of the British Machine Vision Conference 2017, 2017


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