Carles Matabosch

A review of recent range image registration methods with accuracy evaluation

The three-dimensional reconstruction of real objects is an important topic in computer vision. Most of the acquisition systems are limited to reconstruct a partial view of the object obtaining in blind areas and occlusions, while in most applications a full reconstruction is required. Many authors have proposed techniques to fuse 3D surfaces by determining the motion between the different views. The first problem is related to obtaining a rough registration when such motion is not available. The second one is focused on obtaining a fine registration from an initial approximation. In this paper, a survey of the most common techniques is presented. Furthermore, a sample of the techniques has been programmed and experimental results are reported to determine the best method in the presence of noise and outliers, providing a useful guide for an interested reader including a Matlab toolbox available at the webpage of the authors.

Overview of coded light projection techniques for automatic 3D profiling

Obtaining automatic 3D profile of objects is one of the most important issues in computer vision. With this information, a large number of applications become feasible: from visual inspection of industrial parts to 3D reconstruction of the environment for mobile robots. In order to achieve 3D data, range finders can be used. Coded structured light approach is one of the most widely used techniques to retrieve 3D information of an unknown surface. An overview of the existing techniques as well as a new classification of patterns for structured light sensors is presented. This kind of systems belong to the group of active triangulation method, which are based on projecting a light pattern and imaging the illuminated scene from one or more points of view. Since the patterns are coded, correspondences between points of the image(s) and points of the projected pattern can be easily found. Once correspondences are found, a classical triangulation strategy between camera(s) and projector device leads to the reconstruction of the surface. Advantages and constraints of the different patterns are discussed.

Implementation of a robust coded structured light technique for dynamic 3D measurements

This paper presents the implementation details of a coded structured light system for rapid shape acquisition of unknown surfaces. Such techniques are based on the projection of patterns onto a measuring surface and grabbing images of every projection with a camera. Analyzing the pattern deformations that appear in the images, 3D information of the surface can be calculated. The implemented technique projects a unique pattern so that it can be used to measure moving surfaces. The structure of the pattern is a grid where the color of the slits are selected using a De Bruijn sequence. Moreover, since both axis of the pattern are coded, the cross points of the grid have two codewords (which permits to reconstruct them very precisely), while pixels belonging to horizontal and vertical slits have also a codeword. Different sets of colors are used for horizontal and vertical slits, so the resulting pattern is invariant to rotation. Therefore, the alignment constraint between camera and projector considered by a lot of authors is not necessary.

Range image registration for industrial inspection

Building of three-dimensional models is an important topic in computer vision. Range finders only let to reconstruct a partial view of the object. However, in most part of applications a full reconstruction is required. Many authors have proposed several techniques to register 3D surfaces from multiple views. In this paper, a survey of the most common techniques is presented. Furthermore experimental results are performed, and a 3D model is obtained.

Registration of surfaces minimizing error propagation for a one-shot multi-slit hand-held scanner

We propose an algorithm for the on-line automatic registration of multiple 3D surfaces acquired in a sequence by a new hand-held laser scanner. The laser emitter is coupled with an optical lens that spreads the light forming 19 parallel slits that are projected to the scene and acquired with subpixel accuracy by a camera. Splines are used to interpolate the acquired profiles to increase the sample of points and Delaunay triangulation is used to obtain the normal vectors at every point. A point-to-plane pair-wise registration method is proposed to align the surfaces in pairs while they are acquired, conforming paths and eventually cycles that are minimized once detected. The algorithm is specially designed for on-line applications and can be classified as a closing-the-loop technique, where there are not that many competing methods, though it has been compared to the literature. Experiments providing qualitative and quantitative evaluation are shown by means of synthetic and real data and we demonstrated the reliability of our technique.

Surface registration from range image fusion

The registration of full 3-D models is an important task in computer vision. Range finders only reconstruct a partial view of the object. Many authors have proposed several techniques to register 3D surfaces from multiple views in which there are basically two aspects to consider. First, poor registration in which some sort of correspondences are established. Second, accurate registration in order to obtain a better solution. A survey of the most common techniques is presented and includes experimental results of some of them.

Overview of surface registration techniques including loop minimization for three-dimensional modeling and visual inspection

3D modeling is an important topic concerning visual inspection in automatic quality control. Through visual inspection, it is possible to determine whether a product fulfills the required specifications or whether it contains surface or volume imperfections. Although some processes such as color analysis can be achieved by 2D techniques, more challenging tasks such as volume inspection of large and complex objects/scenes may require the use of accurate 3D registration techniques. 3D simultaneous localization and mapping has become a very important research topic not only in the robotics field for solving problems such as robot navigation and mapping of 2D/3D scenarios but also in the computer vision community for the estimation of the camera pose and the registration of large-scale objects. Although their techniques differ slightly depending on the application, both communities tend to solve similar problems by means of different approaches. We present a survey of the techniques used by the robotics and computer vision communities, pointing out the pros and cons and potential applications of each approach. Furthermore, the most representative techniques have been programmed and tested, obtaining experimental results that provide an accurate comparison of the methods in the presence of noise and outliers.

A refined range image registration technique for multi-stripe laser scanner

Nowadays, visual inspection is very important in the quality control for many industrial applications. However, the complexity of most 3D objects constrains the registration of range images; a complete surface is required to compare the acquired surface to the model. Range finders are very used to digitalize free form shape objects with large resolutions. Moreover, one single view is not enough to reconstruct the whole surface due to occlusions, shadows, etc. In these situations, the motion between reconstructed partial views are required to integrate all surfaces in a single model. However, the use of positioning systems is not always available or adequate due mainly to the size of the objects or the environmental conditions imposed by the precise mechanics which suffer from vibrations present in the industry. In order to solve this problem, a 3D hand sensor is developed to reconstruct 3D objects that let us to compare them with respect the original one.

Summarizing Image/Surface Registration for 6DOF Robot/Camera Pose Estimation

In recent years, 6 Degrees Of Freedom (DOF) Pose Estimation and 3D Mapping is becoming more important not only in the robotics community for applications such as robot navigation but also in computer vision for the registration of large surfaces such as buildings and statues. In both situations, the robot/camera position and orientation must be estimated in order to be used for further alignment of the 3D map/surface. Although the techniques differ slightly depending on the application, both communities tend to solve similar problems by means of different approaches. This article is a guide for any scientist interested in the field since the surveyed techniques have been compared pointing out their pros and cons and their potential applications.

Overview of 3D registration techniques including loop minimization for the complete acquisition of large manufactured parts and complex environments

3D modelling is becoming an important research topic for visual inspection in automatic quality control. Through visual inspection it is possible to determine whether a product fulfills the required specifications or whether it contains surface or volume imperfections. Although some process such as color analysis can be achieved by 2D techniques, more challenging tasks such as volume inspection of large and complex objects/scenes may require the use of accurate 3D registration techniques. 3D Simultaneous Localization and Mapping has become a very important research topic not only in the computer vision community for quality control applications but also in the robotics field for solving problems such as robot navigation and registration of large surfaces. Although their techniques differ slightly depending on the application, both communities tend to solve similar problems by means of different approaches. This paper presents a survey of the techniques used by the robotics and computer vision communities in which every approach has been compared pointing out their pros and cons and their potential applications.