3D scanning

Summary

3D scanner is the process of analyzing a real-world object or environment to collect three dimensional data of its shape and possibly its appearance (e.g. color). The collected data can then be used to construct digital 3D models. A 3D scanner can be based on many different technologies, each with its own limitations, advantages and costs. Many limitations in the kind of objects that can be digitised are still present. For example, optical technology may encounter many difficulties with dark, shiny, reflective or transparent objects. For example, industrial computed tomography scanning, structured-light 3D scanners, LiDAR and Time Of Flight 3D Scanners can be used to construct digital 3D models, without destructive testing. Collected 3D data is useful for a wide variety of applications. These devices are used extensively by the entertainment industry in the production of movies and video games, including virtual reality. Other common applications of this technology include augmented

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3D scanning is a technique that permits to recover the pixel depth and thus, the three-dimensional shape of an object. This technique is well known since about 25 years ago, but we have seen it coming back recently due to the rapid progress in image processing technology (availability of hight resolution cameras, increase in computing power or increase of storage capacity for example, see \cite{hist}). A 3D scanner works relatively similar as a camera but it measures the depth along the color for every pixels and thus, allows to be used in design process, construction industry, civil engineering, entertainment, archaeology and in case of this project, Art. An non exhaustive list of such technology are laser, Modulated light, photometric stereo and structured light system. In all cases, the principle is based on triangulation, strength/weakness or time of flight. Of course, each techniques comes with its own limitations, advantages and costs. For the purpose of this project, we studied the structured light system. LCAV1559050917

2015

The Lausanne ClearPET demonstrator is one of the new generation of high resolution small animal PET scanners. A high resolution PET scanner aims to maximize the signal-to-noise ratio measured in pixels for a given time without compromising spatial resolution. In order to achieve it, ClearPET scanners are based on phoswich technology : two different crystals (LSO and LuYAP) are aligned one behind the other and coupled to the same channel of a multichannel photo-detector. Depth-of-interaction is determined by a pulse shape analysis. To improve the prototype design, a Monte Carlo simulation toolkit dedicated to emission tomography – GATE – was created. The accurate description of time-dependent phenomena such as source or detector movement and source decay kinetics represents the most important feature of this software. The first part of this work presents the demonstrator built in Lausanne, mainly the DAQ process and the libraries for the data treatment, and the GATE functionality. In the second part, the measurements obtained with the ClearPET demonstrator combined with simulations are presented. The simulations allow estimation of the performance of a final scanner and refinement of the detector head design. Measurements as well as simulations give a spatial resolution of 1.3 mm on the scanner axis and 2.5 mm at 4 cm from the axis. Temporal resolution for two modules with the same sampling phase is about 4.3 ns for LSO and 4.9 ns for LuYAP. For a standard acquisition, the energy resolution at 511 keV is about 31 ± 4 % for LSO and 33 ± 8 % for LuYAP. The peaks at full energy before calibration are about 480 ± 50 keV1 for LSO and 470 ± 40 keV1 for LuYAP. These variations, coupled with hardware threshold, are one of the main reasons for the sensitivity and count rate performance limitations. A sensitivity of 4.37 ± 0.05 is estimated for a full ring design with four rings of detector modules. The large systematic errors are induced by the variability previously mentioned. ------------------------------ 1 As spectra are not normalized, keV unities are inappropriate. Channel numbers are more accurate.

EPFL2007

Face rendering is a really important topic in Computer Graphics because a lot of virtual simulations or video games contain virtual humans. In order to obtain a realistic face, we need to take care of skin rendering. Nowadays, we can use modern 3D scanning technology to obtain very detailed meshes and textures for the face but the main difficulty with skin rendering is that we need to model subsurface scattering effects. In 2007, d'Eon, Eugene, David Luebke, and Eric Enderton published the article "Efficient Rendering of Human Skin" that describe an algorithm for rendering realistic skin in real-time. The goal of my work was to implement their algorithm to simulate subsurface scattering in skin. I also implemented diffuse environment lighting with occlusions using spherical harmonics.

2011