My research interests are in the fields of computer vision and machine learning, with a focus on learning effective video representations for dynamic scene understanding. In particular, I plan to explore computational theories that represent spatiotemporal visual information, within a confluence of machine vision and learning. I aim to find efficient solutions for problems that are grounded in applications such as recognition and detection from video.
Moritz Kampelmuehler, 2017 (MSc level): Camera-based Vehicle Velocity Estimation
Horst Fuchs, 2017 (MSc level): Visualizing and Understanding Deep Driving Models
Roland Mulczet, 2017 (BSc level): Measuring the Invisible with Laser Speckles
Oliver Papst, 2017 (BSc level): 3D Object Detection for Road Scene Understanding
Gerhard Neuhold, 2015 (MSc; now at Mapillary): Pedestrian Detection with Convolutional Neural Networks