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Plane-Based Optimization of Geometry and Texture for RGB-D Reconstruction of Indoor Scenes

机译:基于平面优化的RGB-D重建室内场景的几何和纹理

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We present a novel approach to reconstruct RGB-D indoor scene with plane primitives. Our approach takes as input a RGB-D sequence and a dense coarse mesh reconstructed by some 3D reconstruction method on the sequence, and generate a lightweight, low-polygonal mesh with clear face textures and sharp features without losing geometry details from the original scene. To achieve this, we firstly partition the input mesh with plane primitives, simplify it into a lightweight mesh next, then optimize plane parameters, camera poses and texture colors to maximize the photometric consistency across frames, and finally optimize mesh geometry to maximize consistency between geometry and planes. Compared to existing planar reconstruction methods which only cover large planar regions in the scene, our method builds the entire scene by adaptive planes without losing geometry details and preserves sharp features in the final mesh. We demonstrate the effectiveness of our approach by applying it onto several RGB-D scans and comparing it to other state-of-the-art reconstruction methods.
机译:我们提出了一种用平面基元重建RGB-D室内场景的新方法。我们的方法用作序列上的某些3D重建方法重建的RGB-D序列和重新设计的密集粗网格,并产生具有清晰的面纹理和尖锐特征的轻质,低多边形网格,而不会从原始场景中失去几何细节。为此,我们首先将输入网格与平面基元分区,将其简化为轻量级网格,然后优化平面参数,相机姿势和纹理颜色,以最大化帧的光度一致性,并最终优化几何之间的一致性以最大化一致性和飞机。与现有的平面重建方法相比,仅在场景中覆盖大平面区域,我们的方法通过自适应平面构建整个场景,而不会损失几何细节,并在最终网格中保留尖锐的功能。我们通过将其应用到几个RGB-D扫描并将其与其他最先进的重建方法进行比较来证明我们的方法的有效性。

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