Digital twins

Today 580 million people in Internet have a profile in virtual worlds. In a virtual world the player represents an individual and takes on a role. Your digital alter ego interacts with other people online and live. It is a lasting world because it will still exist even if you abandon it. One prediction is that in 2012 one billion Internet users will be connected to virtual social nets. This perspective for the future has shown a new business niche. This niche is orientated to satisfy the basic requirements of the cybernetic population: To generate a characterised Digital Twin for every user. There are two common methodologies to create your Digital Twin. The first one is by choosing preset configurations like hair colour, sex, high and weight. This originates a similar pattern of your real person. The second one is by 'pasting' a dimensional picture in to a generic 3D model, whose movements are limited by the incongruity between face and body. NUUME, a company located in Barcelona, has was the first one to propose the creation of an avatar which photo-realistic in order to identify yourself in your virtual relationships.Peer ReviewedPostprint (published version

Dress-Me-Up: A Dataset & Method for Self-Supervised 3D Garment Retargeting

We propose a novel self-supervised framework for retargeting non-parameterized 3D garments onto 3D human avatars of arbitrary shapes and poses, enabling 3D virtual try-on (VTON). Existing self-supervised 3D retargeting methods only support parametric and canonical garments, which can only be draped over parametric body, e.g. SMPL. To facilitate the non-parametric garments and body, we propose a novel method that introduces Isomap Embedding based correspondences matching between the garment and the human body to get a coarse alignment between the two meshes. We perform neural refinement of the coarse alignment in a self-supervised setting. Further, we leverage a Laplacian detail integration method for preserving the inherent details of the input garment. For evaluating our 3D non-parametric garment retargeting framework, we propose a dataset of 255 real-world garments with realistic noise and topological deformations. The dataset contains $44$ unique garments worn by 15 different subjects in 5 distinctive poses, captured using a multi-view RGBD capture setup. We show superior retargeting quality on non-parametric garments and human avatars over existing state-of-the-art methods, acting as the first-ever baseline on the proposed dataset for non-parametric 3D garment retargeting

To Affinity and Beyond: Interactive Digital Humans as a Human Computer Interface

The field of human computer interaction is increasingly exploring the use of more natural, human-like user interfaces to build intelligent agents to aid in everyday life. This is coupled with a move to people using ever more realistic avatars to represent themselves in their digital lives. As the ability to produce emotionally engaging digital human representations is only just now becoming technically possible, there is little research into how to approach such tasks. This is due to both technical complexity and operational implementation cost. This is now changing as we are at a nexus point with new approaches, faster graphics processing and enabling new technologies in machine learning and computer vision becoming available. I articulate the issues required for such digital humans to be considered successfully located on the other side of the phenomenon known as the Uncanny Valley. My results show that a complex mix of perceived and contextual aspects affect the sense making on digital humans and highlights previously undocumented effects of interactivity on the affinity. Users are willing to accept digital humans as a new form of user interface and they react to them emotionally in previously unanticipated ways. My research shows that it is possible to build an effective interactive digital human that crosses the Uncanny Valley. I directly explore what is required to build a visually realistic digital human as a primary research question and I explore if such a realistic face provides sufficient benefit to justify the challenges involved in building it. I conducted a Delphi study to inform the research approaches and then produced a complex digital human character based on these insights. This interactive and realistic digital human avatar represents a major technical undertaking involving multiple teams around the world. Finally, I explored a framework for examining the ethical implications and signpost future research areas

From Physical to Digital, From Interactive to Immersive: Archaeological Uses of 3D, AR, VR, and More

The combination of improved methods and tools, widespread adoption, and continuously-falling barriers to entry has prompted the claim that we are currently living in a ‘golden age of digital archaeology’. This paper provides a background discussion of the use and evolution of digital methods and tools in archaeology, as well as a summary of the conference session “From Physical to Digital, from Interactive to Immersive: Uses of Three– Dimensional Representation, Mixed Reality, and More in the Sharing and Exploration of Archaeological Data,” held at the CAA 2017 conference in Atlanta

Development and implementation of a web-enabled 3D consultation tool for breast augmentation surgery based on 3D-image reconstruction of 2D pictures

Producing a rich, personalized Web-based consultation tool for plastic surgeons and patients is challenging

Exploring Virtual Reality and Doppelganger Avatars for the Treatment of Chronic Back Pain

Cognitive-behavioral models of chronic pain assume that fear of pain and subsequent avoidance behavior contribute to pain chronicity and the maintenance of chronic pain. In chronic back pain (CBP), avoidance of movements often plays a major role in pain perseverance and interference with daily life activities. In treatment, avoidance is often addressed by teaching patients to reduce pain behaviors and increase healthy behaviors. The current project explored the use of personalized virtual characters (doppelganger avatars) in virtual reality (VR), to influence motor imitation and avoidance, fear of pain and experienced pain in CBP. We developed a method to create virtual doppelgangers, to animate them with movements captured from real-world models, and to present them to participants in an immersive cave virtual environment (CAVE) as autonomous movement models for imitation. Study 1 investigated interactions between model and observer characteristics in imitation behavior of healthy participants. We tested the hypothesis that perceived affiliative characteristics of a virtual model, such as similarity to the observer and likeability, would facilitate observers’ engagement in voluntary motor imitation. In a within-subject design (N=33), participants were exposed to four virtual characters of different degrees of realism and observer similarity, ranging from an abstract stickperson to a personalized doppelganger avatar designed from 3d scans of the observer. The characters performed different trunk movements and participants were asked to imitate these. We defined functional ranges of motion (ROM) for spinal extension (bending backward, BB), lateral flexion (bending sideward, BS) and rotation in the horizontal plane (RH) based on shoulder marker trajectories as behavioral indicators of imitation. Participants’ ratings on perceived avatar appearance were recorded in an Autonomous Avatar Questionnaire (AAQ), based on an explorative factor analysis. Linear mixed effects models revealed that for lateral flexion (BS), a facilitating influence of avatar type on ROM was mediated by perceived identification with the avatar including avatar likeability, avatar-observer-similarity and other affiliative characteristics. These findings suggest that maximizing model-observer similarity may indeed be useful to stimulate observational modeling. Study 2 employed the techniques developed in study 1 with participants who suffered from CBP and extended the setup with real-world elements, creating an immersive mixed reality. The research question was whether virtual doppelgangers could modify motor behaviors, pain expectancy and pain. In a randomized controlled between-subject design, participants observed and imitated an avatar (AVA, N=17) or a videotaped model (VID, N=16) over three sessions, during which the movements BS and RH as well as a new movement (moving a beverage crate) were shown. Again, self-reports and ROMs were used as measures. The AVA group reported reduced avoidance with no significant group differences in ROM. Pain expectancy increased in AVA but not VID over the sessions. Pain and limitations did not significantly differ. We observed a moderation effect of group, with prior pain expectancy predicting pain and avoidance in the VID but not in the AVA group. This can be interpreted as an effect of personalized movement models decoupling pain behavior from movement-related fear and pain expectancy by increasing pain tolerance and task persistence. Our findings suggest that personalized virtual movement models can stimulate observational modeling in general, and that they can increase pain tolerance and persistence in chronic pain conditions. Thus, they may provide a tool for exposure and exercise treatments in cognitive behavioral treatment approaches to CBP

{3D} Morphable Face Models -- Past, Present and Future

In this paper, we provide a detailed survey of 3D Morphable Face Models over the 20 years since they were first proposed. The challenges in building and applying these models, namely capture, modeling, image formation, and image analysis, are still active research topics, and we review the state-of-the-art in each of these areas. We also look ahead, identifying unsolved challenges, proposing directions for future research and highlighting the broad range of current and future applications

Men’s Jeans Fit Based on Body Shape Categorization

The purpose of this study was to categorize lower body shape in men and to investigate the interplay between body shape and fitting issues appearing in men’s jeans. More specifically, the goal of the study was to improve apparel fit based on body shape. The detailed objectives of the study were to: (1) Categorize male body shapes using statistical analysis; (2) use 3D virtual fitting technology to assess fit and develop a shape-driven pants block pattern for each body shape. This quantitative study was conducted in three stages: (1) categorizing the body shape of 1420 male scans, aged 18-35, from the SizeUSA dataset, (2) develop a shape-driven pants block pattern for each identified body shape, and (3) validate the developed blocks by virtually trying the shape-driven block pattern on fit testers from different body shape groups. Exploratory Factor Analysis (EFA) and cluster analysis were used for body shape categorization, which resulted in three different body shapes: (1) Flat-Straight, (2) Moderate Curvy-Straight, and (3) Curvy. Three fit models were selected from each identified body shape group and then patterns were developed using Armstrong’s (2005) jeans foundation method. Patterns were modified and fitted to the selected representative fit models of each body shape group. The developed shape-driven block patterns were simulated on the fit testers to further explore the relationship between body shape and fit issues. This study suggests that two individuals with identical body measurements may experience very different fit problems tailored to their different body shapes. It was found that each body shape would exclusively experience unique fit issues. Furthermore, the shape driven block patterns were found to be highly correlated with their host body shape category. This research implies that if the mass customization process starts with block patterns that are engineered for specific body shape categories significantly less fit issues would appear and the desired fit would be achieved in fewer fitting sessions

Women's self-perceptions: an exploratory study of optical illusion garments

Although previous research provides insight into how women construct and idealize their appearance through clothing, the connection to the design elements of a garment is lacking. Using an exploratory approach, the current study, theoretically grounded in the self-discrepancy theory, investigated a woman's perceptions of her body shape. The primary goal of this exploratory study was to understand how garments created with optical illusion prints or patterns, can affect women's perceptions of body shape and if optical illusion garments can increase body satisfaction while helping a woman achieve the appearance of a more ideal body shape. Fifteen women were body scanned to determine their body shape and then participated in an in-depth semi-structured interview while viewing a personalized avatar (created from their body scan) depicted in the seven different optical illusion garments created by the researcher. Data analysis revealed seven themes: (1) Perception of Self, (2) Clothing and the Body, (3) Defining Ideals, (4) Optical Illusion Applications, (5) Preferences by Body Shape Category, (6) Effects of Wearing Optical Illusions, and (7) A More Ideal Self. Results from this study showed that optical illusion garments do effect the visual perception of body shape and can result the perception of a more ideal body shape