Laser point cloud contains only intensity information and it is necessary for visual interpretation to obtain color information from other sensor. Cameras can provide texture, color, and other information of the corresponding object. Points with color information of corresponding pixels in digital images can be used to generate color point-cloud and is conducive to the visualization, classifica...

Splatting-based rendering techniques are currently the best choice for efficient high quality rendering of pointbased geometries. However, such techniques are not suitable for large magnification, especially when the object is under-sampled. This paper improves the rendering quality of pure splatting techniques using a fast dynamic up-sampling algorithm for point-based geometry. Our algorithm i...

In this paper, a new method for constructing NURBS surfaces from scattered and unorganized points is presented. The method is easy to implement and allows fitting a NURBS surface to a scattered point cloud without constructing either NURBS patches networks or polygon meshes. Based on the projection of the points onto the regression plane of the cloud, the method detects both regions where the c...

Point clouds are one of the most primitive and fundamental manifold representations. A popular source of point clouds are three-dimensional shape acquisition devices such as laser range scanners. Another important field where point clouds are found is the representation of high-dimensional manifolds by samples. With the increasing popularity and very broad applications of this source of data, i...

Abstract. In this paper, we consider the harmonic extension problem, which is widely used in many applications of machine learning. We formulate the harmonic extension as solving a LaplaceBeltrami equation with Dirichlet boundary condition. We use the point integral method (PIM) proposed in [14, 19, 13] to solve the Laplace-Beltrami equation. The basic idea of the PIM method is to approximate t...

In this paper we present a progressive compression method for point sampled models that is specifically apt at dealing with densely sampled surface geometry. The compression is lossless and therefore is also suitable for storing the unfiltered, raw scan data. Our method is based on an octree decomposition of space. The point-cloud is encoded in terms of occupied octree-cells. To compress the oc...

Recent development of laser scanning device increased the capability of representing rock outcrop in a very high resolution. Accurate 3D point cloud model with rock joint information can help geologist to estimate stability of rock slope on-site or off-site. An automatic plane extraction method was developed by computing normal directions and grouping them in similar direction. Point normal was...

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Registration of scanned point clouds is the process of integrating two separate local point clouds into one global coordinate system. This process is a key stage in robotic vision SLAM[1], [2], 3D scan to model matching[3] and precision navigation with noisy GPS input. New data acquisition technology such as LIDAR laser scanners mounted on vehicle or aircraft enables for the capture of high qua...

The paper proposed a new 3-D measurement point cloud splicing algorithm. The algorithm utilizes registration ideal in model identification technology to realize unbound and accurate splicing of 3-D data. First, sample the overlapping areas in the two 3-D point clouds which need to be spliced. Carry out preprocessing over the sampled point cloud with principal analysis method based on the statis...