Leibniz Universität Hannover
phone: +49 511 762-5038
fax: +49 511 762-5333
office location: room 232
Bastian Wandt studied Mechatronics at the Leibniz Universität Hannover. During his bachelor studies he focused on robotics and automation. He received his B. Sc. in 2012 with a thesis on path planning of autonomous mobile robots. His master thesis "Ganganalyse in monokularen Bildsequenzen mittels eines morphable Shape-Motion-Models" dealt with 3D reconstruction and animation.
Since 2014 he is working towards his Dr.-Ing. at the Institut für Informationsverarbeitung (TNT). His main research interests are human motion capture and 3D reconstruction. A special focus lies on the application of various machine learning approaches such as dimensionality reduction, compressed sensing, and deep learning for neural networks. His current research analyses deep neural networks for human pose reconstruction.
Show selected publications only
A Kinematic Chain Space for Monocular Motion Capture
ECCV Workshops, September 2018
Extending HEVC with a Texture Synthesis Framework using Detail-aware Image Decomposition
Picture Coding Symposium, June 2018
Detail-aware image decomposition for an HEVC-based texture synthesis framework
Data Compression Conference (DCC), March 2018
Physics-based Models for Human Gait Analysis
Handbook of Human Motion, Springer International Publishing, 2018, edited by Bertram Müller, Sebastian I. Wolf
Extending HEVC Using Texture Synthesis
IEEE Visual Communications and Image Processing (VCIP), St. Petersburg, Florida, USA, December 2017
Optical Flow-based 3D Human Motion Estimation from Monocular Video
German Conference on Pattern Recognition (GCPR), September 2017
Joint 3D Human Motion Capture and Physical Analysis from Monocular Videos
The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, July 2017
3D Reconstruction of Human Motion from Monocular Image Sequences
Transactions on Pattern Analysis and Machine Intelligence, IEEE, Vol. 38, No. 8, pp. 1505-1516, 2016
3D Human Motion Capture from Monocular Image Sequences
IEEE Conference on Computer Vision and Pattern Recognition Workshops, IEEE, June 2015
- Klassifikation menschlicher Bewegungen in Unterräumen (2017)
- Modellierung eines Posenraums menschlicher Bewegungen mit Hilfe neuronaler Netze (2017)
2014-2017: "Tracking und Matching in Bildsequenzen"
since 2017: "Machine Learning"