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Publication Authors

Prof. Dr. Didier Stricker

Dr. Alain Pagani

Dr. Gerd Reis

Eric Thil

Keonna Cunningham

Dr. Oliver Wasenmüller

Dr. Gabriele Bleser

Dr. Jason Raphael Rambach

Dr. Bertram Taetz

Sk Aziz Ali

Rashed Al Koutayni
Yuriy Anisimov

Jilliam Maria Diaz Barros

Ramy Battrawy
Hammad Butt

Mahdi Chamseddine
Steve Dias da Cruz

Fangwen Shu

Torben Fetzer

Michael Fürst

Christiano Couto Gava

Tewodros Amberbir Habtegebrial
Khurram Hashmi

Jigyasa Singh Katrolia

Andreas Kölsch
Onorina Kovalenko

Stephan Krauß
Paul Lesur

Muhammad Jameel Nawaz Malik
Michael Lorenz

Mina Ameli

Nareg Minaskan Karabid

Pramod Murthy

Mathias Musahl

Peter Neigel

Manthan Pancholi
María Alejandra Sánchez Marín
Dr. Kripasindhu Sarkar

Alexander Schäfer

René Schuster

Mohamed Selim

Dennis Stumpf

Yongzhi Su

Xiaoying Tan
Yaxu Xie
Murad Almadani

Ahmet Firintepe

Dr. Vladislav Golyanik

Dr. Aditya Tewari

André Luiz Brandão
SceneFlowFields: Dense Interpolation of Sparse Scene Flow Correspondences
SceneFlowFields: Dense Interpolation of Sparse Scene Flow Correspondences
René Schuster, Oliver Wasenmüller, Georg Kuschk, Christian Bailer, Didier Stricker
IEEE Winter Conference on Applications of Computer Vision (WACV-18), March 12-14, Lake Tahoe, NV/CA, USA
- Abstract:
- While most scene flow methods use either variational optimization or a strong rigid motion assumption, we show for the first time that scene flow can also be estimated by dense interpolation of sparse matches. To this end, we find sparse matches across two stereo image pairs that are detected without any prior regularization and perform dense interpolation preserving geometric and motion boundaries by using edge information. A few iterations of variational energy minimization are performed to refine our results, which are thoroughly evaluated on the KITTI benchmark and additionally compared to state-of-the-art on MPI Sintel. For application in an automotive context, we further show that an optional ego-motion model helps to boost performance and blends smoothly into our approach to produce a segmentation of the scene into static and dynamic parts.