YanyanLi

Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

Yanyan Li

Yanyan

Contact

PhD student, Technische Universität München
Fakultät für Informatik
Boltzmannstr. 3
85748 Garching b. München
Germany
Room: MI 03.13.035
Email: yanyan.li@tum.de

News

  • Oct 15 (2020): 1 Paper pushed to arXiv
  • Sep 9 (2020): 1 Paper accepted to RA-L
  • Jul 2 (2020): 1 Paper accepted to RA-L/IROS' 20

Student Project

Feel free to contact me if you're interested in a bachelor's or master's thesis related to my research areas.

Available
ProjectSelf-supervised Monocular Depth Estimation with Structure Regularities
(Yanyan Li, Federico Tombari)

Running
ProjectReconstructing the MI. Building in a Day
(Yanyan Li, Federico Tombari)

Finished
Master ThesisindoorSLAM: Robust RGB-D SLAM based on Plane-Line-Point features for indoor scenes
(Yanyan Li, Federico Tombari)

Teaching

Research topics

  • Camera pose estimation for robots and autonomous-driving cars based on geometric and learning methods.
  • Geometric prediction and understanding.

Publications

2020
Y. Li, N. Brasch, Y. Wang, N. Navab, F. Tombari
Structure-SLAM: Low-Drift Monocular SLAM in Indoor Environments
International Conference on Intelligent Robots and Systems (IROS), October 25-29, 2020. Las Vegas, USA.
The first two authors contributed equally.
(bib)

TOPIC: Indoor SLAM [slides]

Structure-SLAM: Low-Drift Monocular SLAM in Indoor Environments

camp-iros.png

We present a low-drift monocular SLAM method targeting indoor scenarios. Our approach decouples rotation and translation estimation of the tracking process to reduce the long-term drift in indoor environments.

Co-Planar Parametrization for Stereo-SLAM and Visual-Inertial Odometry

camp-iros.png

This work builds an efficient and robust parametrization for co-planar points&lines, which leverages specific geometric constraints to improve camera pose optimization in terms of both efficiency and accuracy.

RGB-D SLAM with Structural Regularities

RGBdSLAM.png

This work builds a SLAM architecture for RGB-D sensors, which makes use of structure regularities of indoor scenes and provides accurate pose estimation and compact mesh on a CPU.


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Title: M.Sc.
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Firstname: Yanyan
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Lastname: Li
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Nationality: China
Languages: English
Groups: Computer Vision
Expertise: Computer Vision
Position: Scientific Staff
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Room: 03.13.035
Telephone: 089 289 19345
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Edit | Attach | Refresh | Diffs | More | Revision r1.30 - 19 Oct 2020 - 09:54 - YanyanLi

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