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首页> 外文期刊>ISPRS International Journal of Geo-Information >Automatic Pose Estimation of Uncalibrated Multi-View Images Based on a Planar Object with a Predefined Contour Model
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Automatic Pose Estimation of Uncalibrated Multi-View Images Based on a Planar Object with a Predefined Contour Model

机译：基于预定义轮廓模型的基于平面对象的未校准多视图图像的自动姿态估计

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摘要

We have presented a framework to obtain camera pose (i.e., position and orientation in the 3D space) with real scale information of the uncalibrated multi-view images and the intrinsic camera parameters automatically. Our framework consists of two key steps. First, the initial value of the intrinsic camera and the pose parameters were extracted from homography estimation based on the contour model of some planar objects. Second, a refinement of the intrinsic camera and pose parameters was operated by the bundle adjustment procedure. Our framework can provide a complete flow of pose estimation of disorderly or orderly uncalibrated multi-view images, which can be used in vision tasks requiring scale information. Real multi-view images were utilized to demonstrate the robustness, flexibility and accuracy of the proposed framework. The proposed framework was also applied in 3D reconstruction.
机译：我们提出了一个框架，该框架可使用未校准的多视图图像的真实比例信息和相机的固有相机参数自动获取相机姿态（即3D空间中的位置和方向）。我们的框架包括两个关键步骤。首先，基于一些平面物体的轮廓模型，从单应估计中提取出固有相机的初始值和姿态参数。其次，通过束调整程序对固有摄像机和姿态参数进行了改进。我们的框架可提供无序或有序未校准多视图图像的姿势估计的完整流程，可用于需要比例尺信息的视觉任务。实际的多视图图像用于证明所提出框架的鲁棒性，灵活性和准确性。拟议的框架还应用于3D重建。

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