In this paper a new method for parameterizing clouds of unorganized points is presented. The proposed method introduces the notion of dynamic base surfaces (DBS) which are dynamically adapted to the three-dimensional shape implied by the clouds of points. The only assumption regarding the cloud of points is the existence of a boundary defined by a closed path of four curves. The proposed method...

: This paper presents cooperative path planning approach for multi UAVs to detect, model and track the shape of a contaminant cloud boundary. The objective of this research study is to manage the resources (airborne sensors) such as to determine the boundary of a cloud and track its motion with minimum information. The dispersing model of the contaminant cloud boundary is based on SCIPUFF. The ...

We present a new method for extracting the feature primitives of a 3D object directly from the point cloud of its surface scan. The objective is to identify a subset of points that provides the same information about the structure and the topology of the object geometry as the point cloud itself. The entire process is carried out with the least human intervention possible. The only information ...

We propose a new method for registering a cloud of points in 2D onto a planar curve. This method does not require the knowledge of an initial guess for the position of the point cloud and proceeds without having to order, smooth out or otherwise process the points of the query point cloud in any way. The method consists in representing the planar curve by an algebraic curve, and in fitting the ...

A point cloud data set, a set of massive and dense coordinate data points sampled from the surface of a physical object, is emerging as a new representation format of 3D shapes. This is mostly attributed to recent advances in the range finding technology of high-speed 3D laser scanning. A typical laser scanned data set often contains millions of data points and this leads to significant computa...

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...

This paper introduces an online density reduction algorithm for non-homogenous multidimensional datasets. This work is motivated by applications in terrain modeling using laser data. Unlike most existing density reduction algorithms, the developed algorithm is designed for sequentially provided data and online implementation. Experimental results are presented for a 3D points cloud with 3 milli...

We present a new method for extracting features of a 3D object targeted to CAD modeling directly from the point cloud of its surface scan. The objective is to obtain an editable CAD model that is manufacturable and describes accurately the structure and topology of the point cloud. The entire process is carried out with the least human intervention possible. First, the point cloud is sliced int...

2D images often contain irregular salient features and interest points with non-integer coordinates. Our skeletonization problem for such a noisy sparse cloud is to summarize the topology of a given 2D cloud across all scales in the form of a graph, which can be used for combining local features into a more powerful object-wide descriptor. We extend a classical Minimum Spanning Tree of a cloud ...