Surface reconstruction means that retrieve the data by scanning an object using a device such as laser scanner and construct it using the computer to gain back the soft copy of data on that particular object. Surface reconstruction is a reverse method. It is very useful when in a particular object original data is missing without doing any backup. Hence, by doing so, the data can be recollected...

2014 Experimental evidence is herein given of lower critical solution temperatures in high salt aqueous solutions of cetylpyridinium and cetyltrimethylammonium bromide, nitrate and chlorate. The critical behaviour of the solutions is followed using static and dynamic light scattering. The unique feature of this transition lies in the unusually large values of the correlation length 03BE (>...

In this paper, we present a simple technique to evaluate the visibility between pairs of points in a scene. In most current rendering algorithms, visibility queries are evaluated exactly. Our approach approximates the visibility value between two points using a point cloud representation of the surfaces in the scene. The computed value is a function of the distance and orientation of points in ...

Given a collection of unorganised points in space, we present a new method of constructing a surface which approximates this point cloud. The surface is defined implicitly as the isosurface of a trivariate volume model. The volume model is piecewise linear and obtained as a least squares fit to data derived from the point cloud. The original point cloud input is assigned a zero value. Additiona...

Point cloud simplification has become a vital step in any point-based surface processing pipeline. This paper describes a fast and effective algorithm for point cloud simplification with feature preservation. First, feature points are extracted by thresholding curvatures; Second, for non-feature points, they are covered by distinct balls, the points in each ball are substituted by an optimized ...

Geometric searching is an element of mesh generation, interpolation, visualization, collision detection, and many other tasks. The task is searching a cloud of points for the nearest point to a target or all cloud points within a specified distance from a target. This is inherently a O(N) search problem for each query if all N cloud points points are interrogated. Fortunately, this complexity c...

The reconstruction of 3D objects from a point-cloud is based on sufficient separation of the points representing objects of interest from the points of other, unwanted objects. This operation called segmentation is discussed in this paper. We present an interactive unstructured pointcloud segmentation based on graph cut method where the cost function is derived from euclidean distance of point-...

This paper presents Point Convolutional Neural Networks (PCNN): a novel framework for applying convolutional neural networks to point clouds. The framework consists of two operators: extension and restriction, mapping point cloud functions to volumetric functions and viseversa. A point cloud convolution is defined by pull-back of the Euclidean volumetric convolution via an extensionrestriction ...

The Global Ozone Monitoring Experiment (GOME) on board the ERS-2 isdesigned to measure trace gas column densities in the Earth's atmosphere. Such retrievals are hindered by the presence of clouds. The most important cloud parameters that are needed to correct trace gas column density retrievals for the disturbing effects of clouds are the (effective) cloud fraction and cloud top pressure. At pr...

Automatic registration is one of the key technologies for remote sensing image processing.Considering the influence of cloud points, the phenomenon of uneven distributed control points and other problems in the process of registration for the widely used AVHRR remote sensing images, an automatic registration method for AVHRR remote sensing images is proposed. In this method, the cloud points ar...