Computer-supported movement guidance: investigating visual/visuotactile guidance and informing the design of vibrotactile body-worn interfaces

This dissertation explores the use of interactive systems to support movement guidance, with applications in various fields such as sports, dance, physiotherapy, and immersive sketching. The research focuses on visual, haptic, and visuohaptic approaches and aims to overcome the limitations of traditional guidance methods, such as dependence on an expert and high costs for the novice. The main contributions of the thesis are (1) an evaluation of the suitability of various types of displays and visualizations of the human body for posture guidance, (2) an investigation into the influence of different viewpoints/perspectives, the addition of haptic feedback, and various movement properties on movement guidance in virtual environments, (3) an investigation into the effectiveness of visuotactile guidance for hand movements in a virtual environment, (4) two in-depth studies of haptic perception on the body to inform the design of wearable and handheld interfaces that leverage tactile output technologies, and (5) an investigation into new interaction techniques for tactile guidance of arm movements. The results of this research advance the state of the art in the field, provide design and implementation insights, and pave the way for new investigations in computer-supported movement guidance

Technologies and Applications for Big Data Value

This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas. The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part “Technologies and Methods” contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part “Processes and Applications” details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry. The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems

Advanced Sensing and Image Processing Techniques for Healthcare Applications

This Special Issue aims to attract the latest research and findings in the design, development and experimentation of healthcare-related technologies. This includes, but is not limited to, using novel sensing, imaging, data processing, machine learning, and artificially intelligent devices and algorithms to assist/monitor the elderly, patients, and the disabled population

Technologies and Applications for Big Data Value

This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas. The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part “Technologies and Methods” contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part “Processes and Applications” details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry. The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems

Designing a Contactless, AI System to Measure the Human Body using a Single Camera for the Clothing and Fashion Industry

Using a single RGB camera to obtain accurate body dimensions rather than measuring these manually or via more complex multi-camera or more expensive 3D scanners, has a high application potential for the apparel industry. In this thesis, a system that estimates upper human body measurements using a set of computer vision and machine learning techniques. The main steps involve: (1) using a portable camera; (2) improving image quality; (3) isolating the human body from the surrounding environment; (4) performing a calibration step; (5) extracting body features from the image; (6) indicating markers on the image; (7) producing refined final results. In this research, a unique geometric shape is favored, namely the ellipse, to approximate human body main cross sections. We focus on the upper body horizontal slices (i.e. from head to hips) which, we show, can be well represented by varying an ellipse’s eccentricity, this per individual. Then, evaluating each fitted ellipse’s perimeter allows us to obtain better results than the current state-of-the-art for use in the fashion and online retail industry. In our study, I selected a set of two equations, out of many other possible choices, to best estimate upper human body horizontal cross sections via perimeters of fitted ellipses. In this study, I experimented with the system on a diverse sample of 78 participants. The results for the upper human body measurements in comparison to the traditional manual method of tape measurements, when used as a reference, show ±1cm average differences, sufficient for many applications, including online retail

Generation of Virtual Humans for Virtual Reality, Medicine, and Domestic Assistance

Achenbach J. Generation of Virtual Humans for Virtual Reality, Medicine, and Domestic Assistance. Bielefeld: Universität Bielefeld; 2019.Virtual humans are employed in various applications including computer games, special effects in movies, virtual try-ons, medical surgery planning, and virtual assistance. This thesis deals with virtual humans and their computer-aided generation for different purposes. In a first step, we derive a technique to digitally clone the face of a scanned person. Fitting a facial template model to 3D-scanner data is a powerful technique for generating face avatars, in particular in the presence of noisy and incomplete measurements. Consequently, there are many approaches for the underlying non-rigid registration task, and these are typically composed from very similar algorithmic building blocks. By providing a thorough analysis of the different design choices, we derive a face matching technique tailored to high-quality reconstructions from high-resolution scanner data. We then extend this approach in two ways: An anisotropic bending model allows us to more accurately reconstruct facial details. A simultaneous constrained fitting of eyes and eyelids improves the reconstruction of the eye region considerably. Next, we extend this work to full bodies and present a complete pipeline to create animatable virtual humans by fitting a holistic template character. Due to the careful selection of techniques and technology, our reconstructed humans are quite realistic in terms of both geometry and texture. Since we represent our models as single-layer triangle meshes and animate them through standard skeleton-based skinning and facial blendshapes, our characters can be used in standard VR engines out of the box. By optimizing computation time and minimizing manual intervention, our reconstruction pipeline is capable of processing entire characters in less than ten minutes. In a following part of this thesis, we build on our template fitting method and deal with the problem of inferring the skin surface of a head from a given skull and vice versa. Starting with a method for automated estimation of a human face from a given skull remain, we extend this approach to bidirectional facial reconstruction in order to also estimate the skull from a given scan of the skin surface. This is based on a multilinear model that describes the correlation between the skull and the facial soft tissue thickness on the one hand and the head/face surface geometry on the other hand. We demonstrate the versatility of our novel multilinear model by estimating faces from given skulls as well as skulls from given faces within just a couple of seconds. To foster further research in this direction, we made our multilinear model publicly available. In a last part, we generate assistive virtual humans that are employed as stimuli for an interdisciplinary study. In the study, we shed light on user preferences for visual attributes of virtual assistants in a variety of smart home contexts

3DBody Software Experimental Platform for Course of Sports Anatomy

Sports anatomy is one of the important basic subjects of sports colleges and universities. As multimedia network technology increasingly matures and is popularized, it becomes an irresistible trend to transform the traditional teaching mode of sports anatomy into multimedia network teaching mode. Thus, a new-type experimental platform based on action-orientated approach and provided with MVC framework and 3DBody experimental software is put forward in this paper, and it is analyzed and interpreted from the aspects of curriculum design principle and function module of the experimental platform, teaching design model of the experimental platform, and teaching and learning methods. These findings indicate the new-type experimental platform designed in this paper is highly spoken of by students for helping improve students’ practical skill and ability and arouse students’ subjective initiative in learning

EMERGING APPLICATIONS IN THE MEASUREMENT OF BODY COMPOSITION AND THEIR RELATIONSHIPS TO DISEASE RISK

Ph.D