Laurent Kneip
Assistant Professor, PI
Information Science and Technology
Shanghai Tech University
China
Biography
Prof Laurent Kneip owns a PhD degree from ETH Zurich, and a Dipl.-Ing. degree from FAU Erlangen. Before joining ShanghaiTech, he was a DECRA Fellow at the Australian National University, and an Associate Investigator of the Australian Centre of Excellence for Robotic Vision. He is a member of IEEE, and a regular publisher at the top international conferences on computer vision and robotics.
Research Interest
Prof Laurent Kneip's research interest lies in computer vision and in particular real-time 3D environment perception solutions for intelligent mobile systems. His efforts reach from more fundamental theoretic investiations in the fields of structure from motion and algebraic geometry down to the more practical questions behind real-time pipelines for solving multi-camera or multi-sensor simultaneous localization and mapping problems. His current focus lies on a broader definition of the concept of SLAM by extending it to higher-order shape representations, joint semantic inference, and dynamic scene understanding. He is the author and maintainer of the open-source library OpenGV.
Publications
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L Kneip, H Li, and Y Seo. UPnP: An optimal O(n) solution to the absolute pose problem with universal applicability. In Proceedings of the European Conference on Computer Vision (ECCV), Zurich, Switzerland, September 2014
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L Kneip, H Li, and Y Seo. UPnP: An optimal O(n) solution to the absolute pose problem with universal applicability. In Proceedings of the European Conference on Computer Vision (ECCV), Zurich, Switzerland, September 2014
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L Oth, P T Furgale, L Kneip, and R Siegwart. Rolling shutter camera calibration. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Portland, USA, June 2013
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T Kazik, L Kneip, J Nikolic, M Pollefeys, and R Siegwart. Real-time 6D stereo visual odometry with non-overlapping fields of view. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Providence, USA, June 2012
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L Kneip, M Chli, and R Siegwart. Robust real-time visual odometry with a single camera and an IMU. In Proceedings of the British Machine Vision Conference (BMVC), Dundee, Scotland, August 2011
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L Kneip, D Scaramuzza, and R Siegwart. A novel parametrization of the perspective-three-point problem for a direct computation of absolute camera position and orientation. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Colorado Springs, USA, June 2011
