TY - GEN
T1 - An Efficient and Reasonably Simple Solution to the Perspective-Three-Point Problem
AU - Yu, Qida
AU - Xu, Guili
AU - Shi, Jiachen
N1 - Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - In this work, we propose an efficient and simple method for solving the perspective-three-point (P3P) problem. This algorithm leans substantially on linear algebra, in which the rotation matrix and translation vector are parameterized as linear combinations of known vectors with particular coefficients. We also show how to avoid degeneracy when performing this algorithm. Moreover, we present an approach to roughly remove invalid solutions based on the orthogonal property of the rotation matrix. The proposed method is simple to implement and easy to understand, with improved results demonstrating that it is competitive with the leading methods in accuracy, but with reduced computational requirements.
AB - In this work, we propose an efficient and simple method for solving the perspective-three-point (P3P) problem. This algorithm leans substantially on linear algebra, in which the rotation matrix and translation vector are parameterized as linear combinations of known vectors with particular coefficients. We also show how to avoid degeneracy when performing this algorithm. Moreover, we present an approach to roughly remove invalid solutions based on the orthogonal property of the rotation matrix. The proposed method is simple to implement and easy to understand, with improved results demonstrating that it is competitive with the leading methods in accuracy, but with reduced computational requirements.
KW - Computer vision
KW - Linear algebra
KW - Perspective-three-point (p3p)
UR - http://www.scopus.com/inward/record.url?scp=85104373770&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-68793-9_4
DO - 10.1007/978-3-030-68793-9_4
M3 - Conference contribution
AN - SCOPUS:85104373770
SN - 9783030687922
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 46
EP - 59
BT - Pattern Recognition. ICPR International Workshops and Challenges, 2021, Proceedings
A2 - Del Bimbo, Alberto
A2 - Cucchiara, Rita
A2 - Sclaroff, Stan
A2 - Farinella, Giovanni Maria
A2 - Mei, Tao
A2 - Bertini, Marco
A2 - Escalante, Hugo Jair
A2 - Vezzani, Roberto
PB - Springer Science and Business Media Deutschland GmbH
T2 - 25th International Conference on Pattern Recognition Workshops, ICPR 2020
Y2 - 10 January 2021 through 11 January 2021
ER -