Prof. Dr. Didier Stricker

Dr. Alain Pagani

Nicole Stephanie Buhlinger

Keonna Cunningham

Dr. Oliver Wasenmüller

Dr. Gabriele Bleser

Dr. Bertram Taetz

Rashed Al Koutayni

Jilliam Maria Diaz Barros

Mahdi Chamseddine

Steve Dias da Cruz

Christiano Couto Gava

Tewodros Amberbir Habtegebrial

Jigyasa Katrolia

Andreas Kölsch

Onorina Kovalenko

Muhammad Jameel Nawaz Malik

Nareg Minaskan Karabid

Manthan Pancholi

Jason Raphael Rambach

María Alejandra Sánchez Marín

Kripasindhu Sarkar

Alexander Schäfer

André Luiz Brandão

Ahmet Firintepe

Vladislav Golyanik

Combining Stereo Disparity and Optical Flow for Basic Scene Flow

Combining Stereo Disparity and Optical Flow for Basic Scene Flow
René Schuster, Christian Bailer, Oliver Wasenmüller, Didier Stricker
Commercial Vehicle Technology Symposium (CVT-18), March 13-15, Kaiserslautern, Germany

Abstract:: Scene flow is a description of real world motion in 3D that contains more information than optical flow. Because of its complexity there exists no applicable variant for real-time scene flow estimation in an automotive or commercial vehicle context that is sufficiently robust and accurate. Therefore, many applications estimate the 2D optical flow instead. In this paper, we examine the combination of top-performing state-of-the-art optical flow and stereo disparity algorithms in order to achieve a basic scene flow. On the public KITTI Scene Flow Benchmark we demonstrate the reasonable accuracy of the combination approach and show its speed in computation.

Keywords:: Automotive, Commercial Vehicle, Flow Fields, Optical Flow, Scene Flow, Semi-global Matching, Stereo

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