Innovative strategies for 3D visualisation using photogrammetry and 3D scanning for mobile phones

3D model generation through Photogrammetry is a modern overlay of digital information representing real world objects in a virtual world. The immediate scope of this study aims at generating 3D models using imagery and overcoming the challenge of acquiring accurate 3D meshes. This research aims to achieve optimised ways to document raw 3D representations of real life objects and then converting them into retopologised, textured usable data through mobile phones. Augmented Reality (AR) is a projected combination of real and virtual objects. A lot of work is done to create market dependant AR applications so customers can view products before purchasing them. The need is to develop a product independent photogrammetry to AR pipeline which is freely available to create independent 3D Augmented models. Although for the particulars of this research paper, the aim would be to compare and analyse different open source SDK’s and libraries for developing optimised 3D Mesh using Photogrammetry/3D Scanning which will contribute as a main skeleton to the 3D-AR pipeline. Natural disasters, global political crisis, terrorist attacks and other catastrophes have led researchers worldwide to capture monuments using photogrammetry and laser scans. Some of these objects of “global importance” are processed by companies including CyArk (Cyber Archives) and UNESCO’s World Heritage Centre, who work against time to preserve these historical monuments, before they are damaged or in some cases completely destroyed. The need is to question the significance of preserving objects and monuments which might be of value locally to a city or town. What is done to preserve those objects? This research would develop pipelines for collecting and processing 3D data so the local communities could contribute towards restoring endangered sites and objects using their smartphones and making these objects available to be viewed in location based AR. There exist some companies which charge relatively large amounts of money for local scanning projects. This research would contribute as a non-profitable project which could be later used in school curriculums, visitor attractions and historical preservation organisations all over the globe at no cost. The scope isn’t limited to furniture, museums or marketing, but could be used for personal digital archiving as well. This research will capture and process virtual objects using Mobile Phones comparing methodologies used in Computer Vision design from data conversion on Mobile phones to 3D generation, texturing and retopologising. The outcomes of this research will be used as input for generating AR which is application independent of any industry or product

Robots for Exploration, Digital Preservation and Visualization of Archeological Sites

Monitoring and conservation of archaeological sites are important activities necessary to prevent damage or to perform restoration on cultural heritage. Standard techniques, like mapping and digitizing, are typically used to document the status of such sites. While these task are normally accomplished manually by humans, this is not possible when dealing with hard-to-access areas. For example, due to the possibility of structural collapses, underground tunnels like catacombs are considered highly unstable environments. Moreover, they are full of radioactive gas radon that limits the presence of people only for few minutes. The progress recently made in the artificial intelligence and robotics field opened new possibilities for mobile robots to be used in locations where humans are not allowed to enter. The ROVINA project aims at developing autonomous mobile robots to make faster, cheaper and safer the monitoring of archaeological sites. ROVINA will be evaluated on the catacombs of Priscilla (in Rome) and S. Gennaro (in Naples)

A Pipeline for Volume Electron Microscopy of the Caenorhabditis elegans Nervous System.

The "connectome," a comprehensive wiring diagram of synaptic connectivity, is achieved through volume electron microscopy (vEM) analysis of an entire nervous system and all associated non-neuronal tissues. White et al. (1986) pioneered the fully manual reconstruction of a connectome using Caenorhabditis elegans. Recent advances in vEM allow mapping new C. elegans connectomes with increased throughput, and reduced subjectivity. Current vEM studies aim to not only fill the remaining gaps in the original connectome, but also address fundamental questions including how the connectome changes during development, the nature of individuality, sexual dimorphism, and how genetic and environmental factors regulate connectivity. Here we describe our current vEM pipeline and projected improvements for the study of the C. elegans nervous system and beyond

Sistema de digitalização 3D usando super-resolução em imagens RGBD

Orientador : Prof. Dr. Luciano SilvaCo-orientadora : Profª. Drª. Olga R. P. BellonDissertação (mestrado) - Universidade Federal do Paraná, Setor de Ciências Exatas, Programa de Pós-Graduação em Informática. Defesa: Curitiba, 10/09/2013Inclui referênciasResumo: Com o advento de novos sensores de profundidade de baixo custo e com o aumento do poder de processamento paralelo das placas gr_a_cas, houve um aumento signi_cativo em pesquisas na _area de reconstru_c~ao 3D em tempo real. No grupo de pesquisa IMAGO, existe um sistema de reconstru_c~ao 3D para a preserva _c~ao digital, adaptado aos scanners a laser de alta resolu_c~ao. Visando aumentar a exibilidade deste sistema, o objetivo deste trabalho _e a amplia_c~ao do atual pipeline de reconstru_c~ao 3D do IMAGO para permitir a cria_c~ao de modelos utilizando os novos sensores em tempo real. Outro objetivo _e a aplica_c~ao de um m_etodo para o tratamento das imagens de baixa qualidade desses sensores, proporcionando modelos reconstru__dos a partir das novas imagens de melhor resolu_c~ao. A principal meta da preserva_c~ao digital _e a _delidade tanto na geometria quanto na textura do modelo _nal, o tempo e custo computacional s~ao objetivos secund_arios. Portanto, o novo pipeline se resume a tr^es etapas: a modelagem geom_etrica em tempo real, a super-resolu_c~ao e a reconstru_c~ao 3D de alto custo. O objetivo da primeira _e proporcionar a captura completa e o armazenamento de todas as imagens, ambos em tempo real, usando o modelo atualizado apenas para guiar o usu_ario. Na segunda etapa, aumentamos a qualidade e resolu_c~ao das imagens capturadas para a cria_c~ao de um modelo mais _dedigno na etapa _nal, a etapa de reconstru_c~ao 3D utilizando o atual sistema do IMAGO.Abstract: With the advent of new low-cost depth sensors and with the increasing parallel processing power of graphics cards, there was a signi_cant increase in research involving the _eld of real-time 3D reconstruction. In the IMAGO research group, there is a 3D reconstruction system for digital preservation, applied to high resolution laser scanners. To increase the exibility of the mentioned system, our goal is to contributes to the expansion of IMAGO's current 3D reconstruction pipeline to enable the creation of models using new real-time depth sensors. Another objective is the employment of a method that process the sensor's low resolution images, providing reconstructed models using higher resolution images. The aim of digital preservation is the accuracy in both geometry and texture for the _nal model, the computational time and cost are secondary goals. Therefore, the new pipeline is summarized in three steps: a real-time geometric modeling, a super-resolution technique, and high-cost geometric modeling. The goal of the _rst step is to provide a complete capture and image storage, using the real-time model to guide the user. In the second step, we increase the quality and resolution of the captured images to create smooth and accurate models in the 3D reconstruction step using IMAGO's current system

Reflectance Transformation Imaging (RTI) System for Ancient Documentary Artefacts

This tutorial summarises our uses of reflectance transformation imaging in archaeological contexts. It introduces the UK AHRC funded project reflectance Transformation Imaging for Anciant Documentary Artefacts and demonstrates imaging methodologies

3D scanning, modelling and printing of ultra-thin nacreous shells from Jericho: a case study of small finds documentation in archaeology

This paper springs out from a collaborative project jointly carried out by the FabLab Saperi&Co and the Museum of Near East, Egypt and Mediterranean of Sapienza University of Rome focused at producing replicas of ultra-thin archeological finds with a sub-millimetric precision. The main technological challenge of this project was to produce models through 3D optical scanning (photogrammetry) and to print faithful replicas with additive manufacturing. The objects chosen for the trial were five extremely fragile and ultra-thin nacreous shells retrieved in Tell es-Sultan/ancient Jericho by the Italian-Palestinian Expedition in spring 2017, temporarily on exhibit in the Museum. The experiment proved to be successful, and the scanning, modeling and printing of the shells also allowed some observations on their possible uses in research and museum activities

3D scanning of cultural heritage with consumer depth cameras

Three dimensional reconstruction of cultural heritage objects is an expensive and time-consuming process. Recent consumer real-time depth acquisition devices, like Microsoft Kinect, allow very fast and simple acquisition of 3D views. However 3D scanning with such devices is a challenging task due to the limited accuracy and reliability of the acquired data. This paper introduces a 3D reconstruction pipeline suited to use consumer depth cameras as hand-held scanners for cultural heritage objects. Several new contributions have been made to achieve this result. They include an ad-hoc filtering scheme that exploits the model of the error on the acquired data and a novel algorithm for the extraction of salient points exploiting both depth and color data. Then the salient points are used within a modified version of the ICP algorithm that exploits both geometry and color distances to precisely align the views even when geometry information is not sufficient to constrain the registration. The proposed method, although applicable to generic scenes, has been tuned to the acquisition of sculptures and in this connection its performance is rather interesting as the experimental results indicate