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RGB-D Multi-view System Calibration for Full 3D Scene Reconstruction

机译:用于完整3D场景重建的RGB-D多视图系统校准

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One of the most crucial requirements for building a multi-view system is the estimation of relative poses of all cameras. An approach tailored for a RGB-D cameras based multi-view system is missing. We propose BAICP+ which combines Bundle Adjustment (BA) and Iterative Closest Point (ICP) algorithms to take into account both 2D visual and 3D shape information in one minimization formulation to estimate relative pose parameters of each camera. BAICP+ is generic enough to take different types of visual features into account and can be easily adapted to varying quality of 2D and 3D data. We perform experiments on real and simulated data. Results show that with the right weighting factor BAICP+ has an optimal performance when compared to BA and ICP used independently or sequentially.
机译:建立多视图系统的最关键要求之一是估计所有摄像机的相对姿势。缺少为基于RGB-D相机的多视图系统量身定制的方法。我们提出了BAICP +,它结合了束调整(BA)和迭代最近点(ICP)算法,以一种最小化公式考虑了2D视觉和3D形状信息,以估计每个摄像机的相对姿态参数。 BAICP +具有足够的通用性,可以考虑不同类型的视觉特征,并且可以轻松地适应2D和3D数据质量的变化。我们对真实和模拟数据进行实验。结果表明,与单独或顺序使用的BA和ICP相比,具有正确的加权因子,BAICP +具有最佳性能。

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