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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
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