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35
The BallPivoting Algorithm for Surface Reconstruction
 IEEE Transactions on Visualization and Computer Graphics
, 1999
"... The BallPivoting Algorithm (BPA) computes a triangle mesh interpolating a given point cloud. Typically the points are surface samples acquired with multiple range scans of an object. The principle of the BPA is very simple: Three points form a triangle if a ball of a userspecified radius touches ..."
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Cited by 207 (14 self)
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The BallPivoting Algorithm (BPA) computes a triangle mesh interpolating a given point cloud. Typically the points are surface samples acquired with multiple range scans of an object. The principle of the BPA is very simple: Three points form a triangle if a ball of a userspecified radius touches them without containing any other point. Starting with a seed triangle, the ball pivots around an edge (i.e. it revolves around the edge while keeping in contact with the edge's endpoints) until it touches another point, forming another triangle. The process continues until all reachable edges have been tried, and then starts from another seed triangle, until all points have been considered. We applied the BPA to datasets of millions of points representing actual scans of complex 3D objects. The relatively small amount of memory required by the BPA, its time efficiency, and the quality of the results obtained compare favorably with existing techniques.
Viewbased Rendering: Visualizing Real Objects From Scanned Range and . . .
 IN EUROGRAPHICS RENDERING WORKSHOP
, 1997
"... Modeling arbitrary real objects is difficult and rendering textured models typically does not result in realistic images. We describe a new method for displaying scanned real objects, called viewbased rendering. The method takes as input a collection of colored range imagescovering the objectand ..."
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Cited by 110 (10 self)
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Modeling arbitrary real objects is difficult and rendering textured models typically does not result in realistic images. We describe a new method for displaying scanned real objects, called viewbased rendering. The method takes as input a collection of colored range imagescovering the objectand creates a collection of partial object models. These partial models are rendered separately using traditional graphics hardware and blended together using various weights and soft zbuffering. We demonstrate interactive viewing of real, nontrivial objects that would be difficult to model using traditional methods.
Topological Noise Removal
"... Meshes obtained from laser scanner data often contain topological noise due to inaccuracies in the scanning and merging process. This topological noise complicates subsequent operations such as remeshing, parameterization and smoothing. We introduce an approach that removes unnecessary nontrivial to ..."
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Cited by 100 (3 self)
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Meshes obtained from laser scanner data often contain topological noise due to inaccuracies in the scanning and merging process. This topological noise complicates subsequent operations such as remeshing, parameterization and smoothing. We introduce an approach that removes unnecessary nontrivial topology from meshes. Using a local wave front traversal, we discover the local topologies of the mesh and identify features such as small tunnels. We then identify nonseparating cuts along which we cut and seal the mesh, reducing the genus and thus the topological complexity of the mesh.
An autonomous mobile robot with a 3D laser range finder for 3D exploration and digitalization of indoor environments
, 2003
"... Digital 3D models of the environment are needed in rescue and inspection robotics, facility managements and architecture. This paper presents an automatic system for gaging and digitalization of 3D indoor environments. It consists of an autonomous mobile robot, a reliable 3D laser range finder and t ..."
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Cited by 86 (22 self)
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Digital 3D models of the environment are needed in rescue and inspection robotics, facility managements and architecture. This paper presents an automatic system for gaging and digitalization of 3D indoor environments. It consists of an autonomous mobile robot, a reliable 3D laser range finder and three elaborated software modules. The first module, a fast variant of the Iterative Closest Points algorithm, registers the 3D scans in a common coordinate system and relocalizes the robot. The second module, a next best view planner, computes the next nominal pose based on the acquired 3D data while avoiding complicated obstacles. The third module, a closedloop and globally stable motor controller, navigates the mobile robot to a nominal pose on the base of odometry and avoids collisions with dynamical obstacles. The 3D laser range finder acquires a 3D scan at this pose. The proposed method allows one to digitalize large indoor environments fast and reliably without any intervention and solves the SLAM problem. The results of two 3D digitalization experiments are presented using a fast octreebased visualization method.
Least squares 3D surface and curve matching
 ISPRS Journal of Photogrammetry and Remote Sensing
, 2005
"... The automatic coregistration of point clouds, representing 3D surfaces, is a relevant problem in 3D modeling. This multiple registration problem can be defined as a surface matching task. We treat it as least squares matching of overlapping surfaces. The surface may have been digitized/sampled poin ..."
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Cited by 60 (13 self)
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The automatic coregistration of point clouds, representing 3D surfaces, is a relevant problem in 3D modeling. This multiple registration problem can be defined as a surface matching task. We treat it as least squares matching of overlapping surfaces. The surface may have been digitized/sampled point by point using a laser scanner device, a photogrammetric method or other surface measurement techniques. Our proposed method estimates the transformation parameters of one or more 3D search surfaces with respect to a 3D template surface, using the Generalized GaussMarkoff model, minimizing the sum of squares of the Euclidean distances between the surfaces. This formulation gives the opportunity of matching arbitrarily oriented 3D surface patches. It fully considers 3D geometry. Besides the mathematical model and execution aspects we address the further extensions of the basic model. We also show how this method can be used for curve matching in 3D space and matching of curves to surfaces. Some practical examples based on the registration of closerange laser scanner and photogrammetric point clouds are presented for the demonstration of the method. This surface matching technique is a generalization of the least squares image matching concept and offers high flexibility for any kind of 3D surface correspondence problem, as well as statistical tools for the analysis of the quality of final matching results.
RealTime Rendering of Real World Environments
, 1999
"... : One of the most important goals of interactive computer graphics is to allow a user to freely walk around a virtual recreation of a real environment that looks as real as the world around us. But handmodeling such a virtual environment is inherently limited and acquiring the scene model using ..."
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Cited by 32 (8 self)
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: One of the most important goals of interactive computer graphics is to allow a user to freely walk around a virtual recreation of a real environment that looks as real as the world around us. But handmodeling such a virtual environment is inherently limited and acquiring the scene model using devices also presents challenges. Interactively rendering such a detailed model is beyond the limits of current graphics hardware, but imagebased approaches can significantly improve the status quo. We present an endtoend system for acquiring highly detailed scans of large real world spaces, consisting of forty to eighty million range and color samples, using a digital camera and laser rangefinder. We explain successful techniques to represent these large data sets as imagebased models and present contributions to imagebased rendering that allow these models to be rendered in real time on existing graphics hardware without sacrificing the high resolution at which the data sets...
Acquisition and Visualization of Colored 3D Objects
 In ICPR
, 1998
"... This paper presents a complete system for scanning the geometry and surface color of a 3D object and for displaying realistic images of the object from arbitrary viewpoints. A stereo system with active light produces several views of dense range and color data. The data is registered and a surface t ..."
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Cited by 30 (0 self)
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This paper presents a complete system for scanning the geometry and surface color of a 3D object and for displaying realistic images of the object from arbitrary viewpoints. A stereo system with active light produces several views of dense range and color data. The data is registered and a surface that approximates the data is constructed. The surface estimate can be fairly coarse, as the appearance of fine detail is recreated by viewdependent texturing of the surface using color images. 1. Introduction Convincing virtual reality environments require realistic object models, but such models are often difficult to construct synthetically. We have built a semiautomatic system that can acquire range data, register it, construct a model that incorporates both geometry and color, and render it from an arbitrary viewpoint. In this paper, we describe the system, emphasizing viewdependent texturing of geometric models. 2. 3D object reconstruction 3D object reconstruction consists of three...
Automatic Model Refinement for 3D Reconstruction with Mobile Robots
 Fraunhofer Institute for Autonomous Intelligent Systems (AIS) Schloss Birlinghoven, D53754 Sankt
, 2003
"... Precise digital 3D models of indoor environments are needed in several applications, e.g., facility management, architecture, rescue and inspection robotics. This paper presents a new algorithm that transforms a 3D volumetric model into a very precise compact 3D map and generates semantic descriptio ..."
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Cited by 23 (3 self)
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Precise digital 3D models of indoor environments are needed in several applications, e.g., facility management, architecture, rescue and inspection robotics. This paper presents a new algorithm that transforms a 3D volumetric model into a very precise compact 3D map and generates semantic descriptions. Our system is composed of a robust, autonomous mobile robot for the automatic data acquisition and a precise, cost effective, high quality 3D laser scanner to gage indoor environments. The reconstruction method consists of reliable scan matching and feature detection algorithms. The 3D scene is matched against a coarse semantic description of general indoor environments and the generated knowledge is used to refine the 3D model.
Least squares 3D surface matching
 IAPRS, 34(5/W16), (on CDROM
, 2004
"... The automatic coregistration of point clouds, representing 3D surfaces, is a relevant problem in 3D modeling. This registration problem can be defined as a surface matching problem. We treat it as least squares matching of overlapping surfaces. The point cloud may have been digitized/sampled point ..."
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Cited by 20 (4 self)
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The automatic coregistration of point clouds, representing 3D surfaces, is a relevant problem in 3D modeling. This registration problem can be defined as a surface matching problem. We treat it as least squares matching of overlapping surfaces. The point cloud may have been digitized/sampled point by point using a laser scanner device, a photogrammetric method or other surface measurement techniques. In the past, several efforts have been made concerning the registration of 3D point clouds. One of the most popular methods is the Iterative Closest Point (ICP) algorithm. Several variations and improvements of the ICP method have been proposed. In photogrammetry there have been some studies on the absolute orientation of stereo models using DEMs (Digital Elevation Model) as control information. These works are known as DEM matching, which corresponds mathematically with least squares image matching. The DEM matching concept is only applied to 2.5D surfaces. 2.5D surfaces have limited value, especially in close range applications. Our proposed method estimates the 3D similarity transformation parameters between two or more fully 3D surface patches, minimizing the Euclidean distances between the surfaces by least squares. This formulation gives the opportunity of matching arbitrarily oriented 3D surface patches. An observation equation is written for each surface element on the template surface patch, i.e. for each sampled point. The geometric relationship between the conjugate surface patches is defined as a 7parameter 3D similarity transformation. The constant term of the adjustment is given by the observation vector whose elements are the Euclidean distances between the template and search surface elements. Since the functional model is nonlinear, the solution is iteratively approaching to a global minimum. The unknown transformation parameters are treated as stochastic quantities using