Liao Yajie, Sun Ying, Li Gongfa, Kong Jianyi, Jiang Guozhang, Jiang Du, Cai Haibin, Ju Zhaojie, Yu Hui, Liu Honghai
Key Laboratory of Metallurgical Equipment and Control Technology, Wuhan University of Science and Technology, Ministry of Education, Wuhan 430081, China.
Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan 430081, China.
Sensors (Basel). 2017 Jun 24;17(7):1491. doi: 10.3390/s17071491.
Camera calibration is a crucial problem in many applications, such as 3D reconstruction, structure from motion, object tracking and face alignment. Numerous methods have been proposed to solve the above problem with good performance in the last few decades. However, few methods are targeted at joint calibration of multi-sensors (more than four devices), which normally is a practical issue in the real-time systems. In this paper, we propose a novel method and a corresponding workflow framework to simultaneously calibrate relative poses of a Kinect and three external cameras. By optimizing the final cost function and adding corresponding weights to the external cameras in different locations, an effective joint calibration of multiple devices is constructed. Furthermore, the method is tested in a practical platform, and experiment results show that the proposed joint calibration method can achieve a satisfactory performance in a project real-time system and its accuracy is higher than the manufacturer's calibration.
相机校准在许多应用中都是一个关键问题,如三维重建、运动结构分析、目标跟踪和人脸对齐等。在过去几十年里,人们提出了许多方法来解决上述问题,并且性能良好。然而,很少有方法针对多传感器(超过四个设备)的联合校准,而这在实时系统中通常是一个实际问题。在本文中,我们提出了一种新颖的方法和相应的工作流程框架,用于同时校准Kinect和三个外部相机的相对位姿。通过优化最终成本函数并为不同位置的外部相机添加相应权重,构建了一种有效的多设备联合校准方法。此外,该方法在实际平台上进行了测试,实验结果表明,所提出的联合校准方法在项目实时系统中能够取得令人满意的性能,并且其精度高于制造商的校准精度。