Paper Info
Title
An Efficient And Accurate Algorithm For The Perspecitve-N-Point Problem
Abstract
In this paper, we address the problem of pose estimation from N 2D/3D point correspondences, known as the Perspective-n-Point (PnP) problem. Although many solutions have been proposed, it is hard to optimize both computational complexity and accuracy at the same time. In this paper, we propose an accurate and simultaneously efficient solution to the PnP problem. Previous PnP algorithms generally involve two sets of unknowns including the depth of each pixel and the pose of the camera. Our formulation does not involve the depth of each pixel. By introducing some intermediate variables, this formulation leads to a fourth degree polynomial cost function with 3 unknowns that only involves the rotation. In contrast to previous works, we do not address this minimization problem by solving the first-order optimality conditions using the off-the-shelf Grobner basis method, as the Grobner basis method may encounter numeric problems. Instead, we present a method based on linear system null space analysis to provide a robust initial estimation for a Newton iteration. Experimental results demonstrate that our algorithm is comparable to the start-of-the-art algorithms in terms of accuracy, and the speed of our algorithm is among the fastest algorithms.
Year
DOI
Venue
2019
10.1109/IROS40897.2019.8968482
2019 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)
Field
DocType
ISSN
Kernel (linear algebra),Linear system,Computer science,Degree of a polynomial,Algorithm,Pose,Pixel,Gröbner basis,Newton's method,Computational complexity theory
Conference
2153-0858
Citations 
PageRank 
References 
0
0.34
0
Authors
2
Name
Order
Citations
PageRank
Lipu Zhou1255.16
Michael Kaess2180799.52