ECE Seminar  - CPnP: Consistent Pose Estimator for Perspective-n-Point Problem with Bias Elimination

2:30pm - 3:30pm
Room 2302 (lift 17/18), Academic Bldg.


The Perspective-n-Point (PnP) problem has been widely studied in both computer vision and photogrammetry societies.  With the development of feature extraction techniques, a large number of feature points might be available in a single shot.  It is promising to devise a consistent estimator, i.e., the estimate can converge to the true camera pose as the number of points increases. To this end, we propose a consistent PnP solver, named CPnP, with bias elimination.  Specifically, linear equations are constructed from the original projection model via measurement model modification and variable elimination, based on which a closed-form least-squares solution is obtained.  We then analyze and subtract the asymptotic bias of this solution, resulting in a consistent estimate.  Additionally, GaussNewton (GN) iterations are executed to refine the consistent solution. Our proposed estimator is efficient in terms of computations—it has O(n) time complexity.  Simulations and real dataset tests show that our proposed estimator is superior to some well-known ones for images with dense visual features, in terms of estimation precision and computing time.

講者/ 表演者:
Dr. Junfeng WU
Chinese University of Hong Kong, Shenzhen

Junfeng Wu received the B.Eng. degree from the Department of Automatic Control, Zhejiang University, Hangzhou, China, and the Ph.D. degree in electrical and computer engineering from Hong Kong University of Science and Technology, Hong Kong, in 2009, and 2013, respectively. From September to December 2013, he was a Research Associate in the Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology. From January 2014 to June 2017, he was a Postdoctoral Researcher in the ACCESS (Autonomic Complex Communication nEtworks, Signals and Systems) Linnaeus Center, School of Electrical Engineering, KTH Royal Institute of Technology, Stockholm, Sweden.  From 2017 to 2021, he was with the College of Control Science and Engineering, Zhejiang University, Hangzhou, China. He is currently an Associate Professor at the School of Data Science, the Chinese University of Hong Kong, Shenzhen.  His research interests include networked control systems, state estimation, and wireless sensor networks, multi-agent systems.  Dr. Wu received the Guan Zhao-Zhi Best Paper Award at the 34th Chinese Control Conference in 2015.  He is a senior member of IEEE.  He has been serving as an associate editor for IEEE Transactions on Control of Network Systems since 2023.