Computer Vision for Autonomous Driving – The Bertha Benz Project

Who and when?
Dr. Markus Enzweiler, Daimler AG Research & Development Environment Perception in Sindelfingen, is going to visit our University on Tuesday, October 14th. His talk will start at 10:30 am in room B 120.

Topic: Computer Vision for Autonomous Driving – The Bertha Benz Project
Recent Mercedes-Benz cars offer a powerful stereo camera system that sets new standards in vehicle safety and comfort. Autonomous driving has become a reality, at least in low speed highway scenarios. This raises hope for a fast evolution of autonomous driving that also extends to rural and urban traffic situations. In August 2013, “Bertha”, a Mercedes-Benz S-Class vehicle with close-to-production sensors, drove fully autonomously from Mannheim to Pforzheim, following the 100km long historic Bertha Benz Memorial Route. Next-generation stereo vision was the main sensing component and as such formed the basis for the comprehensive understanding of complex traffic situations.
This talk will sketch the state-of-the-art in robust computer vision for intelligent vehicles and will present the overall system architecture used for autonomous driving through busy cities.

Dr. Markus Enzweiler received the BSc degree from the Bonn-Rhein-Sieg University of Applied Sciences, the MSc degree from the University of Ulm, and the PhD degree in computer science from the University of Heidelberg. Since 2010, he has been with Daimler Research & Development in Sindelfingen, Germany, where he co-developed the Daimler vision-based pedestrian detection system which is available in recent Mercedes-Benz cars. His current work focuses on statistical models of object appearance with application to scene understanding, object recognition, and autonomous driving in the domain of intelligent vehicles.
He received graduate and PhD scholarships from the Studienstiftung des deutschen Volkes (German National Academic Foundation). Among several best paper awards, he received both the IEEE Intelligent Transportation Systems Society Best PhD Dissertation Award as well as the Uni-DAS Research Award in 2012 for his contributions to computer vision for intelligent vehicles.

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