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3D POINT CLOUD MODEL COLORIZATION BY DENSE REGISTRATION OF DIGITAL IMAGES

机译:3D点云模型彩色数字图像的密集注册

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Architectural heritage is a historic and artistic property which has to be protected, preserved, restored and must be shown to the public. Modern tools like 3D laser scanners are more and more used in heritage documentation. Most of the time, the 3D laser scanner is completed by a digital camera which is used to enrich the accurate geometric informations with the scanned objects colors. However, the photometric quality of the acquired point clouds is generally rather low because of several problems presented below. We propose an accurate method for registering digital images acquired from any viewpoints on point clouds which is a crucial step for a good colorization by colors projection. We express this image-to-geometry registration as a pose estimation problem. The camera pose is computed using the entire images intensities under a photometric visual and virtual servoing (VVS) framework. The camera extrinsic and intrinsic parameters are automatically estimated. Because we estimates the intrinsic parameters we do not need any informations about the camera which took the used digital image. Finally, when the point cloud model and the digital image are correctly registered, we project the 3D model in the digital image frame and assign new colors to the visible points. The performance of the approach is proven in simulation and real experiments on indoor and outdoor datasets of the cathedral of Amiens, which highlight the success of our method, leading to point clouds with better photometric quality and resolution.
机译:建筑遗产是一个历史性和艺术属性,必须受到保护,保存,恢复,并且必须向公众展示。像3D激光扫描仪这样的现代工具越来越多地用于遗产文档。大多数情况下,3D激光扫描仪由数码相机完成,该数字相机用于丰富与扫描对象颜色的准确的几何信息。然而,由于下面呈现的几个问题,所获取点云的光度质量通常相当低。我们提出了一种准确的方法,用于注册从点云上的任何视点获取的数字图像,这是通过颜色投影良好着色的关键步骤。我们将此图像到几何定位称为姿势估计问题。使用光度视觉和虚拟伺服(VVS)框架下的整个图像强度计算相机姿势。自动估计相机外部和内在参数。因为我们估计内在参数,我们不需要关于采用二手数字图像的相机的任何信息。最后,当点云模型和数字图像正确注册时,我们在数字图像框中投影3D模型,并将新颜色分配给可见点。该方法的表现是在展开amiens大教堂的室内和室外数据集上的模拟和实验中证明了突出了我们方法的成功,导致具有更好的光度质量和分辨率的点云。

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