Geometric fusion of multiple sets of overlapping surface measurements is an important problem for complete 3D object or environment modelling. Fusion based on a discrete implicit surface representation enables fast reconstruction for complex object modelling. However, surfaces are represented at a single resolution resulting in impractical storage costs for accurate reconstruction of large obje...

3D reconstruction of geo-objects from their digital images is a time-efficient and convenient way of studying the structural features of the object being modelled. This paper presents a 3D reconstruction methodology which can be used to generate photo-realistic 3D watertight surface of different irregular shaped objects, from digital image sequences of the objects. The 3D reconstruction approac...

The recent advent of increasingly affordable and powerful 3D scanning devices capable of capturing high resolution range data about real-world objects and environments has fueled research into effective 3D surface reconstruction techniques for rendering the raw point cloud data produced by many of these devices into a form that would make it usable in a variety of application domains. This pape...

In this paper we present an adaptation of Neural Gas (NG) for reconstructing 3D-surfaces from point clouds. NG is based on online adaptation according to given data points and constitutes a neural clustering algorithm that is robust with respect to noisy data and efficient, because the runtime depends solely on the accuracy of the surface reconstruction and is independent of the size of the inp...

For the creation of a realistic 3 meter-sized relief globe of the Moon, a detailed height map of the entire lunar surface is required. Available height measurements of the Moon’s surface are too coarse by a factor of 15 for this purpose. The only publicly available source of high-resolution information are photographic images from the Lunar Orbiter IV mission in 1967. We present a shape-from-sh...

Previously, a computationally efficient and geometrically accurate etching simulation was developed to compute contours of constant depth at different time steps [1]. Experimental verification of this early work has been established [2]. However, contours are not amenable to the analysis and design of microsystems, since it is often necessary to determine object interaction and mechanics in whi...

This paper presents a new combinatorial algorithm for surface reconstruction. It is an interactive and incremental algorithm based on a deenition of the strength of a Delaunay triangle. Local topology of a 2D manifold is enforced while Delaunay triangles are inserted into the partially reconstructed surface in the decreasing order of their strength.

Surface reconstruction is the process to achieve three-dimensional complex surface model basically the algorithm used are start algoritm and filtering algoritm to remove the redundancy factor. The proposed system reduces the size in bytes and bad poles to obtain the accurate and efficient output. The base algorithm is applied to obtain a CAD-model from the given ICADM using power crust. The con...

This paper proposes a novel neural-network-based adaptive hybrid-reflectance three-dimensional (3-D) surface reconstruction model. The neural network combines the diffuse and specular components into a hybrid model. The proposed model considers the characteristics of each point and the variant albedo to prevent the reconstructed surface from being distorted. The neural network inputs are the pi...

Surface reconstruction algorithms can ensure correctness of the reconstructed surface by imposing conditions on sampling and by assuming that the given point set satisfies the prescribed conditions. Traditionally, such sampling conditions impose minimum required sampling density for correct reconstruction. Let us assume that no additional information is provided to the reconstruction algorithm ...