An unified framework for 3D fragmented object patching

2003 Conference on Computer Vision and Pattern Recognition Workshop, 2003

In the recent past, fragment matching has been treated in two different approaches, one using curve matching methods and one that compares whole surfaces or volumes, depending on the nature of the broken artefacts. Presented here is a fast, unified method that combines curve matching techniques with a surface matching algorithm to estimate the positioning and respective matching error for the joining of three-dimensional fragmented objects. Combining both aspects of fragment matching, essentially eliminates most of the ambiguities present in each one of the matching problem categories and helps provide more accurate results with low computational cost.

International Journal of Computer Vision, 2008

We propose a novel and efficient surface matching approach for reassembling broken solids as well as for matching assembly components using cluster trees of oriented points. The method rapidly scans through the space of all possible contact poses of the fragments to be (re)assembled using a tree search strategy, which neither relies on any surface features nor requires an initial solution. The new method first decomposes each point set into a binary tree structure using a hierarchical clustering algorithm. Subsequently the fragments are matched pairwise by descending the cluster trees simultaneously in a depth-first fashion. In contrast to the reassemblage of pottery and thin walled artifacts, this paper addresses the problem of matching broken 3D solids on the basis of their 2.5D fracture surfaces, which are assumed to be reasonable large. Our proposed contact area maximization is a powerful common basis for most surface matching tasks, which can be adapted to numerous special applications. The suggested approach is very robust and offers an outstanding efficiency.

Surface reconstruction is an important issue in geometric modelling. It has received a lot of attention in the computer graphics community in recent years because of image technologies development, namely laser scanning technology, and their wide applications in areas such as reverse engineering, product design, medical devices design and archaeology, among others. In building and rehabilitation areas, laser scanning has been widely applied in the field of architecture for the survey of geometric characteristics of historic buildings. The high speed and accuracy of data acquisition allows the reconstitution of 3D models with a level of detail and precision, exceeding conventional techniques. With this work, it is intended to visualize data acquired from 3D laser scanning and develop a crack characterization and modelling algorithm. This study is developed and implemented using Mathematica algebraic and symbolic platform tools, and in a final stage the opensource application Meshlab is used for the global assembly visualization. Concerning the methodology used, the first approach is the development of automatic extraction of several non-disjoint points process, corresponding to a surface portion. After this, two types of filters are used: the first to eliminate redundant points and thus providing a more efficient cloud, the other to detect crack points. Mathematica allowed us to visualize the interpolations surface of the points sample and obtain an approximation of the surface reconstruction.

2000

(EN) We describe an ongoing,research project on efficient methods,for identification and reconstruction of broken objects among,large collections of irregular fragments. Applications include archaeology, art restoration, failure analysis, and other disciplines. Our solution for flat objects uses multi-scale matching,and constrained dynamic,programming.,We are now extending it to curved pottery fragments through computational stereo vision techniques. Keywords: Digital reconstruction, multi-scale matching, pottery

Lecture Notes in Computer Science, 2004

This paper proposes an efficient pairwise surface matching approach for the automatic assembly of 3d fragments or industrial components. The method rapidly scans through the space of all possible solutions by a special kind of random sample consensus (RANSAC) scheme. By using surface normals and optionally simple features like surface curvatures, we can highly constrain the initial 6 degrees of freedom search space of all relative transformations between two fragments. The suggested approach is robust, very time and memory efficient, easy to implement and applicable to all kinds of surface data where surface normals are available (e.g. range images, polygonal object representations, point clouds with neighbor connectivity, etc.).

Mathematical and Computational Solutions for Archaeology, 2012

In this chapter the authors outline some research works characteristic for the application of Signal Processing and Pattern Analysis techniques to the automatic reconstruction / reassembly of fragmented archaeological objects. The studies described in the chapter cover in their application cases a variety of archaeological objects, ranging from documents and wall-paintings to pots and sculptures. Moreover there are distinct approaches in the treatment of these application cases, with some works focusing on the development of a reconstruction methodology of general purpose, while others aim to develop a complete system to treat a specific application problem. The methodologies developed in these studies are outlined in the chapter so as to retain the basic technical elements of each approach that compile the proposed reconstruction algorithmic scheme.

With the development and application of digital scanning equipment, point cloud processing, data modeling and other reverse engineering technology, the restoration of cultural relics has been more convenient. Therefore, the study of how to use computer to assist the restoration, has important historical and practical significance. In this paper, the three-dimensional fragments of the general shape as the object, and based on the boundary point cloud matching, to achieve debris more accurate splicing recovery. The thesis will study the following aspects: 1) In the case of fragments matching, we select the reasonable boundary feature and feature set, and combine the methods in the literature to measure and determine the similarity of two feature sets. To speed up the matching speed, the rational design of the search method, the greatest extent to find the matching part of the feature group. 2) Fragment matching stage, combined with the existing splicing algorithm, to study how to optimize splicing and error detection.

The reassembly of fractured 3D objects from their parts is an important problem in cultural heritage and other domains.We approach reassembly from a geometric matching perspective and propose a pipeline for the automatic solution of the problem, where an efficient and generic three-level coarse-to-fine search strategy is used for the underlying global optimization. Key to the efficiency of our approach is the use of a discretized approximation of the surfaces' distance field, which significantly reduces the cost of distance queries and allows our method to systematically search the global parameter space with minimal cost. The resulting reassembly pipeline provides highly reliable alignment, as demonstrated through the reassembly of fractured objects from their fragments and the reconstruction of 3D objects from partial scans, showcasing the wide applicability of our methodology.

ACM Transactions on Graphics, 2006

We present a system for automatic reassembly of broken 3D solids. Given as input 3D digital models of the broken fragments, we analyze the geometry of the fracture surfaces to find a globally consistent reconstruction of the original object. Our reconstruction pipeline consists of a graph-cuts based segmentation algorithm for identifying potential fracture surfaces, feature-based robust global registration for pairwise matching of fragments, and simultaneous constrained local registration of multiple fragments. We develop several new techniques in the area of geometry processing, including the novel integral invariants for computing multi-scale surface characteristics, registration based on forward search techniques and surface consistency, and a non-penetrating iterated closest point algorithm. We illustrate the performance of our algorithms on a number of real-world examples.

This paper dwells upon the promising 3D technology for mobile robots and automation industry. The first part of the paper describes the design details of our own 3D Time of Flight (TOF) scanning system based on 2D laser range finder. The second part presents a specific segmentation technique for 3D outdoor urban environments by the common detection of plane models. In a few words, the technique separates the raw data into sparse and dense points, followed by the segmentation of the dense points into urban background and foreground objects. In the end we present some experimental results of real-world data-sets taken from the repository 1,2 of the Leibniz University in Hannover, Germany.