Focal Spot, Winter 2006/2007

https://digitalcommons.wustl.edu/focal_spot_archives/1104/thumbnail.jp

Coping with Data Scarcity in Deep Learning and Applications for Social Good

The recent years are experiencing an extremely fast evolution of the Computer Vision and Machine Learning fields: several application domains benefit from the newly developed technologies and industries are investing a growing amount of money in Artificial Intelligence. Convolutional Neural Networks and Deep Learning substantially contributed to the rise and the diffusion of AI-based solutions, creating the potential for many disruptive new businesses. The effectiveness of Deep Learning models is grounded by the availability of a huge amount of training data. Unfortunately, data collection and labeling is an extremely expensive task in terms of both time and costs; moreover, it frequently requires the collaboration of domain experts. In the first part of the thesis, I will investigate some methods for reducing the cost of data acquisition for Deep Learning applications in the relatively constrained industrial scenarios related to visual inspection. I will primarily assess the effectiveness of Deep Neural Networks in comparison with several classical Machine Learning algorithms requiring a smaller amount of data to be trained. Hereafter, I will introduce a hardware-based data augmentation approach, which leads to a considerable performance boost taking advantage of a novel illumination setup designed for this purpose. Finally, I will investigate the situation in which acquiring a sufficient number of training samples is not possible, in particular the most extreme situation: zero-shot learning (ZSL), which is the problem of multi-class classification when no training data is available for some of the classes. Visual features designed for image classification and trained offline have been shown to be useful for ZSL to generalize towards classes not seen during training. Nevertheless, I will show that recognition performances on unseen classes can be sharply improved by learning ad hoc semantic embedding (the pre-defined list of present and absent attributes that represent a class) and visual features, to increase the correlation between the two geometrical spaces and ease the metric learning process for ZSL. In the second part of the thesis, I will present some successful applications of state-of-the- art Computer Vision, Data Analysis and Artificial Intelligence methods. I will illustrate some solutions developed during the 2020 Coronavirus Pandemic for controlling the disease vii evolution and for reducing virus spreading. I will describe the first publicly available dataset for the analysis of face-touching behavior that we annotated and distributed, and I will illustrate an extensive evaluation of several computer vision methods applied to the produced dataset. Moreover, I will describe the privacy-preserving solution we developed for estimating the \u201cSocial Distance\u201d and its violations, given a single uncalibrated image in unconstrained scenarios. I will conclude the thesis with a Computer Vision solution developed in collaboration with the Egyptian Museum of Turin for digitally unwrapping mummies analyzing their CT scan, to support the archaeologists during mummy analysis and avoiding the devastating and irreversible process of physically unwrapping the bandages for removing amulets and jewels from the body

Computer graphics simulation of natural mummification by desiccation

© 2020 The Authors. Computer Animation and Virtual Worlds published by John Wiley & Sons, Ltd. Organic bodies are subject to internal processes after death, causing significant structural, and optical changes. Mummification by desiccation leads to volume shrinkage, skin wrinkling, and discoloration. We propose a method to simulate the process of mummification by desiccation and its effects on the corpse's morphology and appearance. The mummifying body is represented by a layered model consisting of a tetrahedral mesh, representing the volume, plus a high resolution triangle surface mesh representing the skin. The finite element method is used to solve the moisture diffusion and the resulting volume deformations. Skin wrinkling is achieved using position based dynamics. In order to model a visually believable reproduction of the skin coloration changes due to mummification, a skin shading approach is used that considers moisture content, hemoglobin content, and oxygen saturation. The main focus of the work in this article is to recreate the appearance changes of mummification by desiccation, which, to the best of our knowledge, has not been attempted before in computer graphics to this level of realism. The suggested approach is able to model changes in the internal structure and the surface appearance of the body which resemble the postmortem processes of natural mummification by desiccation

Contextual information based multimedia indexing

Master'sMASTER OF ENGINEERIN

MeatSpace

“MeatSpace” is a group of related bodies of work including podcasts, prints and videos produced by working with simulation technologies such as “weak A.I.”, virtual reality, and 3d scans. Collectively the works explore how people relate to these technologies and how they relate to us. They share thematic or process-oriented sensibilities involving a series of rule-based steps that alternate between the procedural and the intentional. “Uncanny” is defined as strangely familiar. Something which falls in the Uncanny Valley feels wrong, but the reasons may be difficult to articulate. “MeatSpace” is an ongoing experiment to see where our own digital reflections fall in an uncanny spectrum of unsettling familiarity. I am continuously assessing the meaning of words like “consciousness and “choice”, wondering if they are simply interpretations of randomness and determinism. So I search for genuine glimmers of agency in technologies from the present and the past to better understand my own. The groupings within “MeatSpace” are titled “The Intrinsia Chatbox” (podcast), “Outside the Chatbox” (podcast), “Sweet Space/Spatial Awareness”(prints, video, augmented reality), “Formulaics”(music videos), and “Texture Maps/Morph Maps” (prints, video). “MeatSpace” uses manipulation of photogrammetry, volumetric video capture, procedural music generation, animations made in virtual reality, and a video podcast which showcases conversations with chatbots. I see these as acts of collaboration and play with the digital world and it’s developing tools and inhabitants. These processes employ both randomness and control, operating between meatspace and the digital world, between comfort and the uncanny valley

Victorian Alchemy

Victorian Alchemy explores nineteenth-century conceptions of ancient Egypt as this extant civilisation was being ‘rediscovered’ in the modern world. With its material remnants somewhat paradoxically symbolic of both antiquity and modernity (in the very currentness of Egyptological excavations), ancient Egypt was at once evocative of ancient magical power and of cutting-edge science, a tension that might be productively conceived of as ‘alchemical’. Allusions to ancient Egypt simultaneously lent an air of legitimacy to depictions of the supernatural while projecting a sense of enchantment onto representations of cutting-edge science. Examining literature and other cultural forms including art, photography and early film, Eleanor Dobson traces the myriad ways in which magic and science were perceived as entwined, and ancient Egypt evoked in parallel with various fields of study, from imaging technologies and astronomy, to investigations into the electromagnetic spectrum and the human mind itself. In so doing, counter to linear narratives of nineteenth-century progress, and demonstrating how ancient Egypt was more than a mere setting for Orientalist fantasies or nightmares, the book establishes how conceptions of modernity were inextricably bound up in the contemporary reception of the ancient world, and suggests how such ideas that took root and flourished in the Victorian era persist to this day

Victorian Alchemy: Science, magic and ancient Egypt

Victorian Alchemy explores nineteenth-century conceptions of ancient Egypt as this extant civilisation was being ‘rediscovered’ in the modern world. With its material remnants somewhat paradoxically symbolic of both antiquity and modernity (in the very currentness of Egyptological excavations), ancient Egypt was at once evocative of ancient magical power and of cutting-edge science, a tension that might be productively conceived of as ‘alchemical’. Allusions to ancient Egypt simultaneously lent an air of legitimacy to depictions of the supernatural while projecting a sense of enchantment onto representations of cutting-edge science. Examining literature and other cultural forms including art, photography and early film, Eleanor Dobson traces the myriad ways in which magic and science were perceived as entwined, and ancient Egypt evoked in parallel with various fields of study, from imaging technologies and astronomy, to investigations into the electromagnetic spectrum and the human mind itself. In so doing, counter to linear narratives of nineteenth-century progress, and demonstrating how ancient Egypt was more than a mere setting for Orientalist fantasies or nightmares, the book establishes how conceptions of modernity were inextricably bound up in the contemporary reception of the ancient world, and suggests how such ideas that took root and flourished in the Victorian era persist to this day

Detection of abandoned objects in crowded environments

With concerns about terrorism and global security on the rise, it has become vital to have in place efficient threat detection systems that will identify potentially dangerous situations, and alert the authorities to take appropriate action. Of particular relevance is the case of abandoned objects in highly crowded areas. This thesis describes a general framework that recognizes the event of someone leaving an object unattended in forbidden areas. Our approach involves the recognition of four sub-events that characterize the activity of interest. When an unaccompanied object is found, the system analyzes its history to determine its most likely owner(s). Through subsequent frames, the system keeps a lookout for the owner, whose presence in or disappearance from the scene defines the status of the object and determines the appropriate course of action. The system was successfully implemented and tested on several standardized datasets.Electrical and Computer Engineerin