Prof. Dr. Didier Stricker

Dr. Alain Pagani

Nicole Stephanie Buhlinger

Keonna Cunningham

Jason Raphael Rambach

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

María Alejandra Sánchez Marín

Kripasindhu Sarkar

Alexander Schäfer

André Luiz Brandão

Ahmet Firintepe

Vladislav Golyanik

Towards Flow Estimation in Automotive Scenarios

Towards Flow Estimation in Automotive Scenarios
René Schuster, Oliver Wasenmüller, Georg Kuschk, Christian Bailer, Didier Stricker
Computer Science in Cars Symposium ACM Chapters Computer Science in Cars Symposium (CSCS-17), Computer Science in Cars Symposium 2017, July 6, Munich, Germany

Abstract:: In this position paper, we discuss different motion estimation methods in general and especially for automotive scenarios. The advantage of 3D scene flow over 2D optical flow is explained by a typical use case. An indirect method for scene flow reconstruction from stereo disparity and optical flow is presented along with its main issue. Further, we describe how a direct estimation can benefit the overall scene flow result. These observations support our statement that research should focus more on direct 3D motion estimation in the future.

Keywords:: Optical flow, Scene flow, Stereo

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