基于三维激光扫描的物体重构建模

物体拍摄环境具有测量数据量大、物体外轮廓信息复杂等特点,采用当前方法能够获得物体精确的三维点云数据,但缺乏颜色和纹理信息,导致物体重构精度不高,真实感较差;为此,提出一种基于三维激光扫描的物体重构建模方法;该方法通过三维激光扫描技术获取物体点云数据,采用显式的欧拉积分方法对物体整个三维曲面进行平滑,依据三角生长法进行物体三维空间三角划分,将物体网格顶点向球面进行映射,由此构造物体三角网格模型,通过迭代最近点算法对物体非同步点云数据初步匹配结果进行精确配准,利用最近点搜索算法将经多视图立体视觉算法优化后的物体颜色信息和三维点云数据坐标相融合;实验结果表明,所提方法可以快速精确地建立物体三维重构模型,验证了所提方法的可行性。

Object Reconstruction Modeling Based on 3D Laser Scanning

The object shooting environment has the characteristics of large amount of measurement data and complex information on the contours of the object. The current method can obtain the accurate 3D point cloud data, but lacks the color and texture information, which leads to the high accuracy of the object reconstruction and the lack of realism. In this paper, a method of object reconstruction based on 3D laser scanning is proposed. The method uses the three-dimensional laser scanning technique to obtain the object point cloud data, uses the explicit Euler integral method to smooth the whole three-dimensional surface of the object, and divides the three-dimensional space of the object according to the triangular growth method, maps the vertex of the object to the spherical surface, In this paper, the triangular mesh model of the object is used to calculate the initial matching result of the non-synchronized point cloud data by the iterative nearest point algorithm. The nearest object search algorithm is used to optimize the object color information and the three-dimensional point Cloud data coordinates. The experimental results show that the proposed method can quickly and accurately establish the 3D reconstruction model of the object, and verify the feasibility of the proposed method.