High-Fidelity 3D Digital Human Head Creation from RGB-D Selfies

We present a fully automatic system that can produce high-fidelity, photo-realistic three-dimensional (3D) digital human heads with a consumer RGB-D selfie camera. The system only needs the user to take a short selfie RGB-D video while rotating his/her head and can produce a high-quality head reconstruction in less than 30 s. Our main contribution is a new facial geometry modeling and reflectance synthesis procedure that significantly improves the state of the art. Specifically, given the input video a two-stage frame selection procedure is first employed to select a few high-quality frames for reconstruction. Then a differentiable renderer-based 3D Morphable Model (3DMM) fitting algorithm is applied to recover facial geometries from multiview RGB-D data, which takes advantages of a powerful 3DMM basis constructed with extensive data generation and perturbation. Our 3DMM has much larger expressive capacities than conventional 3DMM, allowing us to recover more accurate facial geometry using merely linear basis. For reflectance synthesis, we present a hybrid approach that combines parametric fitting and Convolutional Neural Networks (CNNs) to synthesize high-resolution albedo/normal maps with realistic hair/pore/wrinkle details. Results show that our system can produce faithful 3D digital human faces with extremely realistic details. The main code and the newly constructed 3DMM basis is publicly available.

Digital Transformation and Its Impact on Strategic Supremacy Mediating Role of Digital HRM: an Evidence From Palestine

This study aims to identify the impact of digital transformation in achieving strategic sovereignty in a world that is intensely competitive and in a digitalized era. In the study, the human resource management variable serves as an intermediary variable in the relationship between digital transformation and strategic leadership. The study population consists of (420 top and middle) managers in two mobile telecommunications companies in Palestine, namely: Jawwal and Ooredoo. The study is based on the quantitative approach using a proportional stratified sample, as a 201- item questionnaire is developed using the Seven-Point Likert Scale to study the three variables. The independent variable is digital transformation and its dimensions (Business Model, Customer Experience, Digital Processes, and Impact on People), while the dependent variable is Strategic Supremacy including its three dimensions (Scope of Influence, Competitive Configuration, and Competitive Compression), while digital human resources management serves as an intermediate variable. The data contained herein is analyzed by the Smart PLS Program - structural equation modelling (Second Order). The study shows a positive and good impact of digital transformation on strategic supremacy. The same applies to the impact of digital human resources management thereon. The study concludes that even though digital transformation has a very good impact on human resource management, digital human resources management is a mediating variable in the relationship between digital transformation and strategic supremacy, or even a partial mediator.

Digital human factor management

Now culture of manage safety, health and wellbeing in the mining industry needs a scientifically sound new approach to the training process for professionals at all levels. Insufficient qualification of employees and managers in occupational safety, health and wellbeing has a negative impact on the occupational injury rate, and the current occupational safety, health and wellbeing management system does not allow to instill in employees compliance with the requirements for their own safety. To improve the quality of employees training in safe work practices and to ensure their health, safety and wellbeing in processes, a new training process has been developed and implemented based on a video-based continuous learning system. The innovation will make it possible to manage the human factor by improving employees competence, increasing the efficiency of the system OSH management, taking prompt corrective action, reducing injury rates and retaining human resources.

Wildlife in the Digital Anthropocene: Examining human-animal relations through surveillance technologies

Digital surveillance technologies enable a range of publics to observe the private lives of wild animals. Publics can now encounter wildlife from their smartphones, home computers, and other digital devices. These technologies generate public-wildlife relations that produce digital intimacy, but also summon wildlife into relations of care, commodification, and control. Via three case studies, this paper examines the biopolitical implications of such technologically mediated human-animal relations, which are becoming increasingly common and complex in the Digital Anthropocene. Each of our case studies involves a different biopolitical rationale deployed by a scientific-managerial regime: (1) clampdown (wild boar); (2) care (golden eagle); and (3) control (moose). Each of these modalities of biopower, however, is entangled with the other, inaugurating complex relations between publics, scientists, and wildlife. We show how digital technologies can predetermine certain representations of wildlife by encouraging particular gazes, which can have negative repercussions for public-wildlife relations in both digital and offline spaces. However, there remains work to be done to understand the positive public-wildlife relations inaugurated by digital mediation. Here, departing from much extant literature on digital human-animal relations, we highlight some of these positive potentials, notably: voice, immediacy, and agency.

LEGAL VIEW AT A DIGITAL HUMAN BEING

In continuation of previous research, the article offers a legal view at certain features of the digital human being and the formulation de lege ferenda of the special characteristics of a person of the offense. One of the problems is the question about delusion or weakness of will for digital human being, the decision was made by artificial intelligence, which may call into question the fact that there is a factual basis for legal liability. Regarding the digital person, the possibility of escalation of improved intelligence in all spheres of economic, political, corporate, information and military confrontation is argued. It has been proven that artificial intelligence can eliminate the need to think by human and digital human being, and then eliminate the ability to do it.

Producing Synthetic Dataset for Human Fall Detection in AR/VR Environments

Human poses and the behaviour estimation for different activities in (virtual reality/augmented reality) VR/AR could have numerous beneficial applications. Human fall monitoring is especially important for elderly people and for non-typical activities with VR/AR applications. There are a lot of different approaches to improving the fidelity of fall monitoring systems through the use of novel sensors and deep learning architectures; however, there is still a lack of detail and diverse datasets for training deep learning fall detectors using monocular images. The issues with synthetic data generation based on digital human simulation were implemented and examined using the Unreal Engine. The proposed pipeline provides automatic “playback” of various scenarios for digital human behaviour simulation, and the result of a proposed modular pipeline for synthetic data generation of digital human interaction with the 3D environments is demonstrated in this paper. We used the generated synthetic data to train the Mask R-CNN-based segmentation of the falling person interaction area. It is shown that, by training the model with simulation data, it is possible to recognize a falling person with an accuracy of 97.6% and classify the type of person’s interaction impact. The proposed approach also allows for covering a variety of scenarios that can have a positive effect at a deep learning training stage in other human action estimation tasks in an VR/AR environment.

Digital Twin-Driven Human Robot Collaboration Using a Digital Human

Advances are being made in applying digital twin (DT) and human–robot collaboration (HRC) to industrial fields for safe, effective, and flexible manufacturing. Using a DT for human modeling and simulation enables ergonomic assessment during working. In this study, a DT-driven HRC system was developed that measures the motions of a worker and simulates the working progress and physical load based on digital human (DH) technology. The proposed system contains virtual robot, DH, and production management modules that are integrated seamlessly via wireless communication. The virtual robot module contains the robot operating system and enables real-time control of the robot based on simulations in a virtual environment. The DH module measures and simulates the worker’s motion, behavior, and physical load. The production management module performs dynamic scheduling based on the predicted working progress under ergonomic constraints. The proposed system was applied to a parts-picking scenario, and its effectiveness was evaluated in terms of work monitoring, progress prediction, dynamic scheduling, and ergonomic assessment. This study demonstrates a proof-of-concept for introducing DH technology into DT-driven HRC for human-centered production systems.