3D imaging sensors for the acquisition of three dimensional (3D) shapes have created, in recent years, a considerable degree of interest for a number of applications. The miniaturization and integration of the optical and electronic components used to build them have played a crucial role in the achievement of compactness, robustness and flexibility of the sensors. Today, several 3D sensors are available on the market, even in combination with other sensors in a “sensor fusion” approach. An importance equal to that of physical miniaturization has the portability of the measurements, via suitable interfaces, into software environments designed for their elaboration, e.g., CAD-CAM systems, virtual renders, and rapid prototyping tools. In this paper, following an overview of the state-of-art of 3D imaging sensors, a number of significant examples of their use are presented, with particular reference to industry, heritage, medicine, and criminal investigation applications.

https://www.mdpi.com/1424-8220/9/1/568/pdf

State-of-The-Art and Applications of 3D Imaging Sensors in Industry, Cultural Heritage, Medicine, and Criminal Investigation

We present an algorithm that reduces significantly the level of the registration errors between all pairs in a set of range views. This algorithm refines initial estimates of the transformation matrices obtained from either the calibrated acquisition setup or a crude manual alignment. It is an instance of a category of registration algorithms known as iterated closest-point (ICP) algorithms. The algorithm considers the network of views as a whole and minimizes the registration errors of all views simultaneously. This leads to a well-balanced network of views in which the registration errors are equally distributed, an objective not met by previously published ICP algorithms which all process the views sequentially. Experimental results show that this refinement technique improves the calibrated registrations and the quality of the integrated model for complex multi-part objects. In the case of scenes comprising man-made objects of very simple shapes, the basic algorithm faces problems common to all ICP algorithms and so must be extended.

Towards a general multi-view registration technique

This paper presents a new and general solution to the problem of range view integration. The integration problem consists in computing a connected surface model from a set of registered range images acquired from different viewpoints. The proposed method does not impose constraints on the topology of the observed surfaces, the position of the viewpoints, or the number of views that can be merged. The integrated surface model is piecewise estimated by a set of triangulations modeling each canonical subset of the Venn diagram of the set of range views. The connection of these local models by constrained Delaunay triangulations yields g non-redundant surface triangulation describing all surface elements sampled by the set of range views. Experimental results show that the integration technique can be used to build connected surface models of free-form objects. No integrated models built from objects of such complexity have yet been reported in the literature, It is assumed that accurate range views are available and that frame transformations between all pairs of views can be reliably computed. >

A general surface approach to the integration of a set of range views

With ever-more demanding requirements for the accurate manufacture of large components, dimensional measuring techniques are becoming progressively more sophisticated. This review describes some of the more recently developed techniques and the state-of-the-art in the more well-known large-scale dimensional metrology methods. In some cases, the techniques are described in detail, or, where relevant specialist review papers exist, these are cited as further reading. The traceability of the measurement data collected is discussed with reference to new international standards that are emerging. In some cases, hybrid measurement techniques are finding specialized applications and these are referred to where appropriate. © IMechE 2009.

Recent developments in large-scale dimensional metrology

3D reconstruction methods for digital preservation of cultural heritage

High-resolution 3D imaging and modeling is an important application in the heritage field. We describe several demonstration projects conducted in collaboration with museums and conservation agencies.

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Active optical 3D imaging for heritage applications

The National Research Council of Canada (NRC) has developed and patented three high-resolution 3D imaging systems and processing algorithms which have been applied to a wide range of museum and heritage recording applications. The systems have been designed for different imaging applications and, in collaboration with a number of national and international museums and cultural agencies, have been used to scan a wide variety of objects and sites. The objective of this paper is to present a summary of the 3D technology and examples of its heritage applications. Copyright © 2003 John Wiley & Sons, Ltd.

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NRC 3D imaging technology for museum and heritage applications

Introduces a new method for the calibration of a range camera based on active triangulation. The technique is based on a model derived from the geometry of the synchronized scanner. From known positions of a calibration bar, a logistic equation is fitted with values of spot positions read from a linear position detector at a number of angular positions of a scanning mirror. Furthermore, with an approximate form of the general equations describing the geometry, a series of design guidelines are derived to help a designer conduct a preliminary study of a particular range camera. Experimental results demonstrating the technique are found to compare favorably with theoretical predictions. >

/pdf/model-based-calibration-of-a-range-camera-1zf1pie0x7.pdf

R. Baribeau

Papers

Active optical 3D imaging for heritage applications

NRC 3D imaging technology for museum and heritage applications

Model-based calibration of a range camera