Challenges in Monocular Visual Odometry: Photometric Calibration, Motion Bias and Rolling Shutter Effect (bibtex)
by N. Yang, R. Wang, X. Gao and D. Cremers
Reference:
Challenges in Monocular Visual Odometry: Photometric Calibration, Motion Bias and Rolling Shutter Effect (N. Yang, R. Wang, X. Gao and D. Cremers), In In IEEE Robotics and Automation Letters (RA-L) & Int. Conference on Intelligent Robots and Systems (IROS), volume 3, 2018. ([arxiv])
Bibtex Entry:
@article{yang18challenges,
 author = {N. Yang and R. Wang and X. Gao and D. Cremers},
 title = {Challenges in Monocular Visual Odometry: Photometric Calibration, Motion Bias and Rolling Shutter Effect},
 journal = { In IEEE Robotics and Automation Letters (RA-L) & Int. Conference on Intelligent Robots and Systems (IROS)},
 volume = {3},
 issue = {4},
 pages = {2878--2885},
 year = {2018},
 month = {Oct},
 doi = {10.1109/LRA.2018.2846813},
 titleurl = {yang18challenges.pdf},
 keywords = {Brightness;Calibration;Cameras;Feature extraction;Optimization;Robustness;Simultaneous localization and mapping;Localization;SLAM;performance evaluation and benchmarking;vslam},
}
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Challenges in Monocular Visual Odometry: Photometric Calibration, Motion Bias and Rolling Shutter Effect (bibtex)
Challenges in Monocular Visual Odometry: Photometric Calibration, Motion Bias and Rolling Shutter Effect (bibtex)
by N. Yang, R. Wang, X. Gao and D. Cremers
Reference:
Challenges in Monocular Visual Odometry: Photometric Calibration, Motion Bias and Rolling Shutter Effect (N. Yang, R. Wang, X. Gao and D. Cremers), In In IEEE Robotics and Automation Letters (RA-L) & Int. Conference on Intelligent Robots and Systems (IROS), volume 3, 2018. ([arxiv])
Bibtex Entry:
@article{yang18challenges,
 author = {N. Yang and R. Wang and X. Gao and D. Cremers},
 title = {Challenges in Monocular Visual Odometry: Photometric Calibration, Motion Bias and Rolling Shutter Effect},
 journal = { In IEEE Robotics and Automation Letters (RA-L) & Int. Conference on Intelligent Robots and Systems (IROS)},
 volume = {3},
 issue = {4},
 pages = {2878--2885},
 year = {2018},
 month = {Oct},
 doi = {10.1109/LRA.2018.2846813},
 titleurl = {yang18challenges.pdf},
 keywords = {Brightness;Calibration;Cameras;Feature extraction;Optimization;Robustness;Simultaneous localization and mapping;Localization;SLAM;performance evaluation and benchmarking;vslam},
}
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members:yangn

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Nan Yang

PhD student

Technical University of Munich

School of Computation, Information and Technology
Informatics 9
Boltzmannstrasse 3
85748 Garching
Germany

Fax: +49-89-289-17757
Office: 
Mail: yangn@in.tum.de

Find me on Google Scholar, Linkedin.

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Research Interests

My research interests lie in incorporating deep learning into classical visual odometry and SLAM.

Brief Bio

Nan Yang received his Bachelor's degree in Computer Science from Beijing University of Posts and Telecommunications and his Master's degree in Informatics from the Technical University of Munich. Since May 2018, he is a Ph.D. student and senior computer vision researcher in Artisense, a startup co-founded by Prof. Daniel Cremers.

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