We present an algorithm to display enormous unprocessed point clouds at interactive rates without requiring long postprocessing. The novelty here is that we do not make any assumptions about sampling density or availability of normal vectors for the points. This is very important because such information is available only after lengthy postprocessing of scanned datasets, whereas users want to i...

To generate a 3D computer model of a free-form object, multiple range images (point clouds) covering its entire surface are acquired from different viewpoints. These views are then aligned in a common coordinate basis by minimizing the distance error between their corresponding points. Establishing correspondences automatically is an inherently challenging problem due to the lack of any type of...

In recent years, due to the development of three-dimensional scanning technology, the opportunities for real objects to be three-dimensionally measured, taken into the PC as point cloud data, and used for various contents are increasing. However, the point cloud data obtained by three-dimensional scanning has many problems such as data loss due to occlusion or the material of the object to be m...

We present here a real time mobile mapping system mounted on a vehicle. The terrestrial acquisition system is based on a geolocation system and two sensors, namely, a laser scanner and a camera with a fish-eye lens. We produce 3D colored points cloud and textured models of the environment. Once the system has been calibrated, the data acquisition and processing are done “on the way”. This artic...

We present a fast, memory efficient algorithm that generates a manifold triangular mesh S passing through a set of unorganized points P R3. Nothing is assumed about the geometry, topology or presence of boundaries in the data set except that P is sampled from a real manifold surface. The speed of our algorithm is derived from a projection-based approach we use to determine the incident faces on...

Computing curve skeletons of 3D shapes is a challenging task. Recently, a high-potential technique for this task was proposed, based on integrating medial information obtained from several 2D projections of a 3D shape (Livesu et al., 2012). However effective, this technique is strongly influenced in terms of complexity by the quality of a so-called skeleton probability volume, which encodes pot...

Throughout the course of several years, significant progress has been made with regard to the accuracy and performance of pair-wise alignment techniques; however when considering low-resolution scans with minimal pairwise overlap, and scans with high levels of symmetry, the process of successfully performing sequential alignments in the object reconstruction process remains a challenging task. ...

This paper deals with lidar point cloud filtering and classification for modelling the Terrain and more generally for scene segmentation. In this study, we propose to use the well-known K-means clustering algorithm that filters and segments (point cloud) data. The Kmeans clustering is well adapted to lidar data processing, since different feature attributes can be used depending on the desired ...

one of the main features of high throughput computing systems is the availability of high power processing resources. cloud computing systems can offer these features through concepts like pay-per-use and quality of service (qos) over the internet. many applications in cloud computing are represented by workflows. quality of service is one of the most important challenges in the context of sche...

We present a new technique for the simplification of pointsampled geometry without any prior surface reconstruction. Using Fast Marching farthest point sampling for implicit surfaces and point clouds [1], we devise a coarse-tofine uniform or feature-sensitive simplification algorithm with user-controlled density guarantee. The algorithm is computationally and memory efficient, easy to implement...