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Simultaneous Calibration: A Joint Optimization Approach for Multiple Kinect and External Cameras

机译:同时校准:多种Kinect和外部摄像机的联合优化方法

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摘要

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.
机译:相机校准是许多应用中的关键问题,例如3D重建,运动结构,对象跟踪和面部对齐。在过去的几十年中,已经提出了许多方法来很好地解决上述问题。但是,针对多传感器(四个以上设备)的联合校准的方法很少,这通常是实时系统中的实际问题。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,以同时校准Kinect和三个外部相机的相对姿势。通过优化最终成本函数并向不同位置的外部摄像机添加相应的权重,可以构建多个设备的有效联合标定。此外,该方法在实际平台上进行了测试,实验结果表明,所提出的联合标定方法在项目实时系统中可以达到令人满意的性能,其准确性高于制造商的标定。

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