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

3D Human Pose Tracking inside Car using Single RGB Spherical Camera

3D Human Pose Tracking inside Car using Single RGB Spherical Camera
Pramod Murthy, Onorina Kovalenko, Ahmed Elhayek, Christiano Couto Gava, Didier Stricker
ACM Chapters Computer Science in Cars Symposium (CSCS-17), July 6, Munich, Germany

Abstract:: The recent progress in Deep Learning methods in computer vision has resulted in improved Advanced Driver Assistance Systems (ADAS). The goal of ADAS is not only to assist drivers, but also to alert them before dangerous driving maneuvers. ADAS often do not capture human motions to augment it into the driving context. In this work, we attempt to propose a system to track 3D motion of humans (especially drivers) inside a car using single RGB spherical camera. We use a CNN based 3D human pose tracking system to track driver and passengers poses. Finally, we illustrate accurate results in real-time on recorded driving scenes.

Keywords:: 3D Human Pose Tracking, CNN, Human Activity, Deep Learning

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