State of the Art on Stylized Fabrication

© 2018 The Authors Computer Graphics Forum © 2018 The Eurographics Association and John Wiley & Sons Ltd. Digital fabrication devices are powerful tools for creating tangible reproductions of 3D digital models. Most available printing technologies aim at producing an accurate copy of a tridimensional shape. However, fabrication technologies can also be used to create a stylistic representation of a digital shape. We refer to this class of methods as ‘stylized fabrication methods’. These methods abstract geometric and physical features of a given shape to create an unconventional representation, to produce an optical illusion or to devise a particular interaction with the fabricated model. In this state-of-the-art report, we classify and overview this broad and emerging class of approaches and also propose possible directions for future research

Workshop on Smart Sensors - Instrumentation and Measurement: Program

On 18-19 February, the School of Engineering successfully ran a two-day workshop on Smart Sensors - Instrumentation and Measurement. Associate Professor Rainer Künnemeyer organised the event on behalf of the IEEE Instrumentation and Measurement Society, New Zealand Chapter. Over 60 delegates attended and appreciated the 34 presentations which covered a wide range of topics related to sensors, sensor networks and instrumentation. There was substantial interest and support from local industry and crown research institutes

Using Virtual Reality and Remotely Sensed Data to Explore Object Identity and Embodiment in a Virtual Mayan City

3D visualization, LiDAR (Light Detection and Ranging), and 3D modeling are not new concepts in archaeology, however when combined they represent a growing body of research that seeks to understand both how these tools can help us to study the people of the past, and the past itself. Recently, archaeologists have been creating large amounts of 3D digital assets because of new and more advanced technologies. Along with these digital assets has come a myriad of single object viewers—both web and desktop based. These platforms specifically focus on visualizing individual objects (i.e., artifacts or buildings). In contrast, 3DGIS and Virtual Reality (VR) software employ recreated landscapes with multiple 3D objects rather than single 3D models. The MayaCityBuilder Project (http://mayacitybuilder.org) employs Geographic Information Systems (GIS) and LIDAR data to simulate the ancient Maya city of Copan in a virtual space for immersive exploration. Using this environment as a virtual lattice, we embed object data into the actual simulated space of Copan, which users can explore using a virtual reality headset. I propose that such an environment allows us to explore the concept of object identity. Wherein the “objects” in the environment (i.e. 3D models of both remotely sensed extant objects and reconstructed buildings) are immersively evaluated by users who can better perceive the relationships between themselves and the “objects” with which they are interacting; resulting in insights that can push archaeological inquiry in new directions. Further, applying such an approach opens the door for 3D data reuse providing a platform that serves a unique database structure holding intuitive and perceptual data. In order to test these ideas, I embed multiple kinds of 3D models into the Copan VR platform and use the relationships between both the environment and the objects to explain object identity. Advisor: Heather Richards-Rissett

Modeling Ozark Caves with Structure-from-Motion Photogrammetry: An Assessment of Stand-Alone Photogrammetry for 3-Dimensional Cave Survey

Nearly all aspects of karst science and management begin with a map. Yet despite this fact, cave survey is largely conducted in the same archaic way that is has been for years - with a compass, tape measure, and a sketchpad. Traditional cave survey can establish accurate survey lines quickly. However, passage walls, ledges, profiles, and cross-sections are time intensive and ultimately rely on the sketcher’s experience at interpretively hand drawing these features between survey stations. This project endeavors to experiment with photogrammetry as a method of improving on traditional cave survey, while also avoiding some of the major pitfalls of terrestrial laser scanning. The proposed method allows for the creation of 3D models which capture cave wall geometry, important cave formations, as well as providing the ability to create cross sections anywhere desired. The interactive 3D cave models are produced cheaply, with equipment that can be operated in extremely confined, harsh conditions, by unpaid volunteers with little to no technical training. While the rapid advancement of photogrammetric software has led to its use in many 3D modeling applications, there is only a sparse body of research examining the use of photogrammetry as a standalone method for surveying caves. The proposed methodology uses a GoPro camera and a 1000 lumen portable floodlight to capture still images down the length of cave passages. The procedure goes against several traditional rules of thumb, both operating in the dark with a moving light source, as well as utilizing a wide angle, fish eye lens, to capture scene information that is not perpendicular to the camera\u27s field of view. Images are later processed into 3D models using Agisoft’s PhotoScan. Four caves were modeled using the method, with varying levels of success. The best results occurred in dry confined passages, while passages greater than 9 meters (30ft) in width, or those with a great deal of standing water in the floor, produced large holes. An additional experiment occurred in the University of Arkansas utility tunnel

Visions of Substance: 3D Imaging in Mediterranean Archaeology

With the advent of low-cost and easy to use 3D imaging tools, the discipline of archaeology is on the cusp of a major change in how we document, study, and publish archaeological contexts. While there are a growing number of volumes dedicated to this subject, Visions of Substance: 3D Imaging in Mediterranean Archaeology represents an accessible and conversational introduction to the theory and practice of 3D imaging techniques in a Mediterranean and European context

State of the art on stylized fabrication

© 2019 Copyright held by the owner/author(s). Digital fabrication devices are powerful tools for creating tangible reproductions of 3D digital models. Most available printing technologies aim at producing an accurate copy of a tridimensional shape. However, fabrication technologies can also be used to create a stylistic representation of a digital shape. We refer to this class of methods as stylized fabrication methods. These methods abstract geometric and physical features of a given shape to create an unconventional representation, to produce an optical illusion, or to devise a particular interaction with the fabricated model. In this course, we classify and overview this broad and emerging class of approaches and also propose possible directions for future research

Information embedding and retrieval in 3D printed objects

Deep learning and convolutional neural networks have become the main tools of computer vision. These techniques are good at using supervised learning to learn complex representations from data. In particular, under limited settings, the image recognition model now performs better than the human baseline. However, computer vision science aims to build machines that can see. It requires the model to be able to extract more valuable information from images and videos than recognition. Generally, it is much more challenging to apply these deep learning models from recognition to other problems in computer vision. This thesis presents end-to-end deep learning architectures for a new computer vision field: watermark retrieval from 3D printed objects. As it is a new area, there is no state-of-the-art on many challenging benchmarks. Hence, we first define the problems and introduce the traditional approach, Local Binary Pattern method, to set our baseline for further study. Our neural networks seem useful but straightfor- ward, which outperform traditional approaches. What is more, these networks have good generalization. However, because our research field is new, the problems we face are not only various unpredictable parameters but also limited and low-quality training data. To address this, we make two observations: (i) we do not need to learn everything from scratch, we know a lot about the image segmentation area, and (ii) we cannot know everything from data, our models should be aware what key features they should learn. This thesis explores these ideas and even explore more. We show how to use end-to-end deep learning models to learn to retrieve watermark bumps and tackle covariates from a few training images data. Secondly, we introduce ideas from synthetic image data and domain randomization to augment training data and understand various covariates that may affect retrieve real-world 3D watermark bumps. We also show how the illumination in synthetic images data to effect and even improve retrieval accuracy for real-world recognization applications

On the popularization of digital close-range photogrammetry: a handbook for new users.

Εθνικό Μετσόβιο Πολυτεχνείο--Μεταπτυχιακή Εργασία. Διεπιστημονικό-Διατμηματικό Πρόγραμμα Μεταπτυχιακών Σπουδών (Δ.Π.Μ.Σ.) “Γεωπληροφορική