|Laurent Kneip, Assistant Professor|
3D perception for mobile systems
Structure from motion
Visual localization and mapping
Dr Kneip owns a Dipl.-Ing. degree from the Friedrich-Alexander University Erlangen/Nürnberg, and a PhD degree from ETH Zurich, where he worked at the Autonomous Systems Lab. He also is a former recipient of the Discovery Early Career Researcher Award (DECRA) from the Australian Research Council, hosted by the Australian National University, where he remains an honorary senior lecturer. Dr Kneip currently serves as an Assistant Professor tenure-track within the School of Information Science and Technology at ShanghaiTech. He is an expert in computer vision trying to enable autonomous systems and mobile applications to use cameras for real-time 3D perception of the environment. His main research interests include visual odometry/SLAM (Simultaneous Localization and Mapping) and structure from motion with single and multi-camera systems, as well as the efficient solution of the more fundamental, underlying algebraic geometry problems. Dr Kneip is the main author of the open-source project OpenGV.
Campbell D. J., Petersson L., Kneip L. and Li H.,“Globally-Optimal Inlier Set Maximisation for Camera Poseand Correspondence Estimation”, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018.
Zhou Yi, Hongdong Li and Laurent Kneip, “Canny-VO: Visual Odometry With RGB-D Cameras Based on Geometric 3-D–2-D Edge Alignment”, IEEE Transactions on Robotics, 2018.
Briales J., Kneip L. and Gonzalez-Jimenez, “A Certifiably Globally Optimal Solution to the Non-Minimal Relative Pose Problem”, in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 145-154, 2018.
Zhou Y., Gallego G., Rebecq H., Kneip L., Li H. and Scaramuzza, “Semi-dense 3d reconstruction with a stereo event camera”, in Proceedings of the European Conference on Computer Vision (ECCV), pp. 235-251, 2018.
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.
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)
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. 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 2018.
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.
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.