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首页> 外文期刊>IEEE Transactions on Pattern Analysis and Machine Intelligence >Absolute Pose Estimation of Central Cameras Using Planar Regions
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Absolute Pose Estimation of Central Cameras Using Planar Regions

机译:使用平面区域的中央相机的绝对姿态估计

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摘要

A novel method is proposed for the absolute pose estimation of a central 2D camera with respect to 3D depth data without the use of any dedicated calibration pattern or explicit point correspondences. The proposed method has no specific assumption about the data source: plain depth information is expected from the 3D sensing device and a central camera is used to capture the 2D images. Both the perspective and omnidirectional central cameras are handled within a single generic camera model. Pose estimation is formulated as a 2D-3D nonlinear shape registration task which is solved without point correspondences or complex similarity metrics. It relies on a set of corresponding planar regions, and the pose parameters are obtained by solving an overdetermined system of nonlinear equations. The efficiency and robustness of the proposed method were confirmed on both large scale synthetic data and on real data acquired from various types of sensors.
机译:在不使用任何专用校准模式或明确的点对应关系的情况下,提出了一种新的方法,用于对3D深度数据相对于3D深度数据的绝对姿态估计。所提出的方法对数据源没有特定假设:从3D传感设备预期纯度深度信息,并且中央相机用于捕获2D图像。透视和全向中央相机都在单个通用相机模型中处理。构造姿势估计作为2D-3D非线性形状注册任务,该任务在没有点对应关系或复杂的相似度度量的情况下解决。它依赖于一组相应的平面区域,并且通过求解非线性方程的过多系统来获得姿势参数。在大规模合成数据和各种类型传感器中获取的实际数据上确认了所提出的方法的效率和鲁棒性。

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