Calibration Venus: An Interactive Camera Calibration Method Based on Search Algorithm and Pose Decomposition

Cameras are widely used in many scenes such as robot positioning and unmanned driving, in which the camera calibration is a major task in this field. The interactive camera calibration method based on a plane board is becoming popular due to its stability and handleability. However, most methods cho...

Full description

Bibliographic Details
Main Authors: Wentai Lei, Mengdi Xu, Feifei Hou, Wensi Jiang, Chiyu Wang, Ye Zhao, Tiankun Xu, Yan Li, Yumei Zhao, Wenjun Li
Format: Article
Language:English
Published: MDPI AG 2020-12-01
Series:Electronics
Subjects:
Online Access:https://www.mdpi.com/2079-9292/9/12/2170
Description
Summary:Cameras are widely used in many scenes such as robot positioning and unmanned driving, in which the camera calibration is a major task in this field. The interactive camera calibration method based on a plane board is becoming popular due to its stability and handleability. However, most methods choose suggestions subjectively from a fixed pose dataset, which is error-prone and limited for different camera models. In addition, these methods do not provide clear guidelines on how to place the board in the specified pose. This paper proposes a new interactive calibration method, named ‘Calibration Venus’, including two main parts: pose search and pose decomposition. First, a pose search algorithm based on simulated annealing (SA) algorithm is proposed to select the optimal pose in the entire pose space. Second, an intuitive and easy-to-use user guidance method is designed to decompose the optimal pose into four sub-poses: translation, each rotation along <i>X</i>-, <i>Y</i>-, <i>Z</i>-axes. Thereby the users could follow the guide step by step to accurately complete the placement of the calibration board. Experimental results evaluated on simulated and real datasets show that the proposed method can reduce the difficulty of calibration, and improve the accuracy of calibration, as well as provide better guidance.
ISSN:2079-9292