487 research outputs found

    HCI for the deaf community: developing human-like avatars for sign language synthesis

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    With ever increasing computing power and advances in 3D animation technologies it is no surprise that 3D avatars for sign language (SL) generation are advancing too. Traditionally these avatars have been driven by somewhat expensive and inflexible motion capture technologies and perhaps this is the reason avatars do not feature in all but a few user interfaces (UIs). SL synthesis is a competing technology that is less costly, more versatile and may prove to be the answer to the current lack of access for the Deaf in HCI. This paper outlines the current state of the art in SL synthesis for HCI and how we propose to advance this by improving avatar quality and realism with a view to ameliorating communication and computer interaction for the Deaf community as part of a wider localisation project

    Development of the huggable social robot Probo: on the conceptual design and software architecture

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    This dissertation presents the development of a huggable social robot named Probo. Probo embodies a stuffed imaginary animal, providing a soft touch and a huggable appearance. Probo's purpose is to serve as a multidisciplinary research platform for human-robot interaction focused on children. In terms of a social robot, Probo is classified as a social interface supporting non-verbal communication. Probo's social skills are thereby limited to a reactive level. To close the gap with higher levels of interaction, an innovative system for shared control with a human operator is introduced. The software architecture de nes a modular structure to incorporate all systems into a single control center. This control center is accompanied with a 3D virtual model of Probo, simulating all motions of the robot and providing a visual feedback to the operator. Additionally, the model allows us to advance on user-testing and evaluation of newly designed systems. The robot reacts on basic input stimuli that it perceives during interaction. The input stimuli, that can be referred to as low-level perceptions, are derived from vision analysis, audio analysis, touch analysis and object identification. The stimuli will influence the attention and homeostatic system, used to de ne the robot's point of attention, current emotional state and corresponding facial expression. The recognition of these facial expressions has been evaluated in various user-studies. To evaluate the collaboration of the software components, a social interactive game for children, Probogotchi, has been developed. To facilitate interaction with children, Probo has an identity and corresponding history. Safety is ensured through Probo's soft embodiment and intrinsic safe actuation systems. To convey the illusion of life in a robotic creature, tools for the creation and management of motion sequences are put into the hands of the operator. All motions generated from operator triggered systems are combined with the motions originating from the autonomous reactive systems. The resulting motion is subsequently smoothened and transmitted to the actuation systems. With future applications to come, Probo is an ideal platform to create a friendly companion for hospitalised children

    Visualising Human Motion: a First Principles Approach using Vicon data in Maya

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    Author version made available in accordance with publisher copyright policy.This paper describes a first principles approach to understanding how 3D digital animation of human motion can be processed and produced from raw data, without the use of proprietary software. The paper describes how students collected motion data using a custom marker set, how this was used to create a point cloud, how errors were corrected, and finally how the skeleton was rigged, skinned and modelled in Maya

    Investigating User Experience Using Gesture-based and Immersive-based Interfaces on Animation Learners

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    Creating animation is a very exciting activity. However, the long and laborious process can be extremely challenging. Keyframe animation is a complex technique that takes a long time to complete, as the procedure involves changing the poses of characters through modifying the time and space of an action, called frame-by-frame animation. This involves the laborious, repetitive process of constantly reviewing results of the animation in order to make sure the movement-timing is accurate. A new approach to animation is required in order to provide a more intuitive animating experience. With the evolution of interaction design and the Natural User Interface (NUI) becoming widespread in recent years, a NUI-based animation system is expected to allow better usability and efficiency that would benefit animation. This thesis investigates the effectiveness of gesture-based and immersive-based interfaces as part of animation systems. A practice-based element of this research is a prototype of the hand gesture interface, which was created based on experiences from reflective practices. An experimental design is employed to investigate the usability and efficiency of gesture-based and immersive-based interfaces in comparison to the conventional GUI/WIMP interface application. The findings showed that gesture-based and immersive-based interfaces are able to attract animators in terms of the efficiency of the system. However, there was no difference in their preference for usability with the two interfaces. Most of our participants are pleasant with NUI interfaces and new technologies used in the animation process, but for detailed work and taking control of the application, the conventional GUI/WIMP is preferable. Despite the awkwardness of devising gesture-based and immersive-based interfaces for animation, the concept of the system showed potential for a faster animation process, an enjoyable learning system, and stimulating interest in a kinaesthetic learning experience

    Enhancing Expressiveness of Speech through Animated Avatars for Instant Messaging and Mobile Phones

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    This thesis aims to create a chat program that allows users to communicate via an animated avatar that provides believable lip-synchronization and expressive emotion. Currently many avatars do not attempt to do lip-synchronization. Those that do are not well synchronized and have little or no emotional expression. Most avatars with lip synch use realistic looking 3D models or stylized rendering of complex models. This work utilizes images rendered in a cartoon style and lip-synchronization rules based on traditional animation. The cartoon style, as opposed to a more realistic look, makes the mouth motion more believable and the characters more appealing. The cartoon look and image-based animation (as opposed to a graphic model animated through manipulation of a skeleton or wireframe) also allows for fewer key frames resulting in faster speed with more room for expressiveness. When text is entered into the program, the Festival Text-to-Speech engine creates a speech file and extracts phoneme and phoneme duration data. Believable and fluid lip-synchronization is then achieved by means of a number of phoneme-to-image rules. Alternatively, phoneme and phoneme duration data can be obtained for speech dictated into a microphone using Microsoft SAPI and the CSLU Toolkit. Once lip synchronization has been completed, rules for non-verbal animation are added. Emotions are appended to the animation of speech in two ways: automatically, by recognition of key words and punctuation, or deliberately, by user-defined tags. Additionally, rules are defined for idle-time animation. Preliminary results indicate that the animated avatar program offers an improvement over currently available software. It aids in the understandability of speech, combines easily recognizable and expressive emotions with speech, and successfully enhances overall enjoyment of the chat experience. Applications for the program include use in cell phones for the deaf or hearing impaired, instant messaging, video conferencing, instructional software, and speech and animation synthesis

    Modeling variation of human motion

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    The synthesis of realistic human motion with large variations and different styles has a growing interest in simulation applications such as the game industry, psychological experiments, and ergonomic analysis. The statistical generative models are used by motion controllers in our motion synthesis framework to create new animations for different scenarios. Data-driven motion synthesis approaches are powerful tools for producing high-fidelity character animations. With the development of motion capture technologies, more and more motion data are publicly available now. However, how to efficiently reuse a large amount of motion data to create new motions for arbitrary scenarios poses challenges, especially for unsupervised motion synthesis. This thesis presents a series of works that analyze and model the variations of human motion data. The goal is to learn statistical generative models to create any number of new human animations with rich variations and styles. The work of the thesis will be presented in three main chapters. We first explore how variation is represented in motion data. Learning a compact latent space that can expressively contain motion variation is essential for modeling motion data. We propose a novel motion latent space learning approach that can intrinsically tackle the spatialtemporal properties of motion data. Secondly, we present our Morphable Graph framework for human motion modeling and synthesis for assembly workshop scenarios. A series of studies have been conducted to apply statistical motion modeling and synthesis approaches for complex assembly workshop use cases. Learning the distribution of motion data can provide a compact representation of motion variations and convert motion synthesis tasks to optimization problems. Finally, we show how the style variations of human activities can be modeled with a limited number of examples. Natural human movements display a rich repertoire of styles and personalities. However, it is difficult to get enough examples for data-driven approaches. We propose a conditional variational autoencoder (CVAE) to combine large variations in the neutral motion database and style information from a limited number of examples.Die Synthese realistischer menschlicher Bewegungen mit großen Variationen und unterschiedlichen Stilen ist für Simulationsanwendungen wie die Spieleindustrie, psychologische Experimente und ergonomische Analysen von wachsendem Interesse. Datengetriebene Bewegungssyntheseansätze sind leistungsstarke Werkzeuge für die Erstellung realitätsgetreuer Charakteranimationen. Mit der Entwicklung von Motion-Capture-Technologien sind nun immer mehr Motion-Daten öffentlich verfügbar. Die effiziente Wiederverwendung einer großen Menge von Motion-Daten zur Erstellung neuer Bewegungen für beliebige Szenarien stellt jedoch eine Herausforderung dar, insbesondere für die unüberwachte Bewegungssynthesemethoden. Das Lernen der Verteilung von Motion-Daten kann eine kompakte Repräsentation von Bewegungsvariationen liefern und Bewegungssyntheseaufgaben in Optimierungsprobleme umwandeln. In dieser Dissertation werden eine Reihe von Arbeiten vorgestellt, die die Variationen menschlicher Bewegungsdaten analysieren und modellieren. Das Ziel ist es, statistische generative Modelle zu erlernen, um eine beliebige Anzahl neuer menschlicher Animationen mit reichen Variationen und Stilen zu erstellen. In unserem Bewegungssynthese-Framework werden die statistischen generativen Modelle von Bewegungscontrollern verwendet, um neue Animationen für verschiedene Szenarien zu erstellen. Die Arbeit in dieser Dissertation wird in drei Hauptkapiteln vorgestellt. Wir untersuchen zunächst, wie Variation in Bewegungsdaten dargestellt wird. Das Erlernen eines kompakten latenten Raums, der Bewegungsvariationen ausdrucksvoll enthalten kann, ist für die Modellierung von Bewegungsdaten unerlässlich. Wir schlagen einen neuartigen Ansatz zum Lernen des latenten Bewegungsraums vor, der die räumlich-zeitlichen Eigenschaften von Bewegungsdaten intrinsisch angehen kann. Zweitens stellen wir unser Morphable Graph Framework für die menschliche Bewegungsmodellierung und -synthese für Montage-Workshop- Szenarien vor. Es wurde eine Reihe von Studien durchgeführt, um statistische Bewegungsmodellierungs und syntheseansätze für komplexe Anwendungsfälle in Montagewerkstätten anzuwenden. Schließlich zeigen wir anhand einer begrenzten Anzahl von Beispielen, wie die Stilvariationen menschlicher Aktivitäten modelliertwerden können. Natürliche menschliche Bewegungen weisen ein reiches Repertoire an Stilen und Persönlichkeiten auf. Es ist jedoch schwierig, genügend Beispiele für datengetriebene Ansätze zu erhalten. Wir schlagen einen Conditional Variational Autoencoder (CVAE) vor, um große Variationen in der neutralen Bewegungsdatenbank und Stilinformationen aus einer begrenzten Anzahl von Beispielen zu kombinieren. Wir zeigen, dass unser Ansatz eine beliebige Anzahl von natürlich aussehenden Variationen menschlicher Bewegungen mit einem ähnlichen Stil wie das Ziel erzeugen kann

    Evaluation of graphical user interfaces for augmented reality based manual assembly support

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    Augmented reality (AR) technology is advancing rapidly and promises benefits to a wide variety of applications&mdashincluding manual assembly and maintenance tasks. This thesis addresses the design of user interfaces for AR applications, focusing specifically on information presentation interface elements for assembly tasks. A framework was developed and utilized to understand and classify these elements, as well as to evaluate numerous existing AR assembly interfaces from literature. Furthermore, a user study was conducted to investigate the strengths and weaknesses of concrete and abstract AR interface elements in an assembly scenario, as well as to compare AR assembly instructions against common paper-based assembly instructions. The results of this study supported, at least partially, the three hypotheses that concrete AR elements are more suitable to convey part manipulation information than abstract AR elements, that concrete AR and paper-based instructions lead to faster assembly times than abstract AR instructions alone, and that concrete AR instructions lead to greater increases in user confidence than paper-based instructions. The study failed to support the hypothesis that abstract AR elements are more suitable for part identification than concrete AR elements. Finally, the study results and hypothesis conclusions are used to suggest future work regarding interface element design for AR assembly applications

    Application-driven visual computing towards industry 4.0 2018

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    245 p.La Tesis recoge contribuciones en tres campos: 1. Agentes Virtuales Interactivos: autónomos, modulares, escalables, ubicuos y atractivos para el usuario. Estos IVA pueden interactuar con los usuarios de manera natural.2. Entornos de RV/RA Inmersivos: RV en la planificación de la producción, el diseño de producto, la simulación de procesos, pruebas y verificación. El Operario Virtual muestra cómo la RV y los Co-bots pueden trabajar en un entorno seguro. En el Operario Aumentado la RA muestra información relevante al trabajador de una manera no intrusiva. 3. Gestión Interactiva de Modelos 3D: gestión online y visualización de modelos CAD multimedia, mediante conversión automática de modelos CAD a la Web. La tecnología Web3D permite la visualización e interacción de estos modelos en dispositivos móviles de baja potencia.Además, estas contribuciones han permitido analizar los desafíos presentados por Industry 4.0. La tesis ha contribuido a proporcionar una prueba de concepto para algunos de esos desafíos: en factores humanos, simulación, visualización e integración de modelos

    Comparing and Evaluating Real Time Character Engines for Virtual Environments

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    As animated characters increasingly become vital parts of virtual environments, then the engines that drive these characters increasingly become vital parts of virtual environment software. This paper gives an overview of the state of the art in character engines, and proposes a taxonomy of the features that are commonly found in them. This taxonomy can be used as a tool for comparison and evaluation of different engines. In order to demonstrate this we use it to compare three engines. The first is Cal3D, the most commonly used open source engine. We also introduce two engines created by the authors, Piavca and HALCA. The paper ends with a brief discussion of some other popular engines
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