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Laurent Kneip    助理教授、研究员
所在学院 信息科学与技术学院
研究方向 Computer Vision
联系方式 lkneip@@shanghaitech.edu.cn
 
  个人简介  
2003 - 2005 Undergraduate studies at Friedrich-Alexander University, Erlangen-Nuernberg, Germany
2005 - 2008 Graduate studies at Friedrich-Alexander University, Erlangen-Nuernberg, Germany (specialised in mechatronic engineering)
2009 - 2013 PhD studies at ETH Zurich, Switzerland (with Prof Roland Siegwart and Prof Marc Pollefeys)
2013 - 2015 Post-doc, Research School of Engineering, Australina National University (with Prof Richard Hartley and Prof Hongdong Li)
2015 Visiting scholar at ShanghaiTech University (with Prof Ma Yi)
2016 Visiting scholar at University of Zurich (with Prof Davide Scaramuzza)
2015 - 2017 DECRA Fellow, Research School of Engineering, Australian National University
2017.7 - present Assistant Professor, PI, School of Information Sciences and Technology (SIST), ShanghaiTech, China
  主要研究内容  
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.

More can be found on: laurentkneip.com
  代表性论文  
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

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


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

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

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

L Kneip and P Furgale. OpenGV: A unified and generalized approach to calibrated geometric vision. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China, May 2014

G Long,  L Kneip, J M Alvarez, H Li, X Zhang, and Q Yu. Learning Image Matching by Simply Watching Video. In Proceedings of the European Conference on Computer Vision (ECCV), Amsterdam, Netherlands, October 2016

Y Dai, H Li, and L Kneip. Rolling shutter camera relative pose: Generalized epipolar geometry. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, USA, June 2016

D Campbell, L Petersson, L Kneip, and H Li. Globally-Optimal Inlier Set Maximisation for Simultaneous Camera Pose and Feature Correspondence. In Proceedings of the International Conference on Computer Vision (ICCV), Venice, Italy, October 2017

Y Wang and L Kneip. On scale initialization in non-overlapping multi-perspective visual odometry. In Proceedings of the International Conference on Computer Vision Systems, Shenzhen, July 2017. Best Student Paper Award

Y Zhou, L Kneip, and H Li. Semi-dense Visual Odometry for RGB-D Cameras using Approximate Nearest Neighbour Fields. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Singapore, May 2017
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