[IDA ML Seminar] Bastian Wandt: Human Motion and Dynamics Capture with Limited Data. October 12, 15:15-16:15

[Fredrik Lindsten]

Welcome to an IDA Machine Learning Seminar on October 12, 15:15-16:15.

Bastian Wandt<https://liu.se/en/employee/baswa38>, Department of Electrical Engineering (ISY), Linköping University
Human Motion and Dynamics Capture with Limited Data
Abstract: 3D human motion capture has a wide range of applications across society with the most common examples being in movie production, medicine, autonomous driving, and human-robot interaction. In recent years, rapid deep learning driven advances in research have translated directly into commercial products. However, despite successful commercialization, many problems remain for these data-hungry machine learning approaches. Arguably the most important problem is the lack of training data covering the whole variety of human motions; it is even questionable whether such data can ever be recorded. This talk will present several solutions for monocular human motion capture that side-step the problem of missing data by the use of weakly- or unsupervised machine learning techniques in combination with geometric modeling. It will also give a glimpse on future applications in motion analysis by capturing human dynamics, i.e. forces and torques on and inside the human body.

Location: Ada Lovelace<http://www.ida.liu.se/department/location/search.en.shtml?keyword=ada>
Organizer: Fredrik Lindsten, Sourabh Balgi

Speaker Bio: Bastian Wandt is a WASP Assistant Professor at the Computer Vision Laboratory, Department of Electrical Engineering, Linköping University. Prior to this he was a Postdoc at the University of British Columbia in the group of Helge Rhodin. He got his PhD degree from Leibniz University of Hannover in 2020. His main research interests are human motion capture and 3D reconstruction. A special focus lies on the application of machine learning techniques such as deep learning, dimensionality reduction and compressed sensing. His current research analyses weakly supervised training of deep neural networks for human pose reconstruction. He studied Mechatronics at the Leibniz Universität Hannover. During the bachelor studies he focused on robotics and received a B. Sc. in 2012 with a thesis on path planning of autonomous mobile robots. His master thesis Gait Analysis in Monocular Image Sequences using a Morphable Shape Motion Model dealt with 3D reconstruction and animation of human motions. In 2018 he founded the AI consulting company HEUWA together with a colleague from TNT.


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Welcome!
IDA Machine Learning Group
Linköping University

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