Real Time Animation of Virtual Humans: A Trade-off Between Naturalness and Control

Virtual humans are employed in many interactive applications using 3D virtual environments, including (serious) games. The motion of such virtual humans should look realistic (or ‘natural’) and allow interaction with the surroundings and other (virtual) humans. Current animation techniques differ in the trade-off they offer between motion naturalness and the control that can be exerted over the motion. We show mechanisms to parametrize, combine (on different body parts) and concatenate motions generated by different animation techniques. We discuss several aspects of motion naturalness and show how it can be evaluated. We conclude by showing the promise of combinations of different animation paradigms to enhance both naturalness and control

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

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

Expressive movement generation with machine learning

Movement is an essential aspect of our lives. Not only do we move to interact with our physical environment, but we also express ourselves and communicate with others through our movements. In an increasingly computerized world where various technologies and devices surround us, our movements are essential parts of our interaction with and consumption of computational devices and artifacts. In this context, incorporating an understanding of our movements within the design of the technologies surrounding us can significantly improve our daily experiences. This need has given rise to the field of movement computing – developing computational models of movement that can perceive, manipulate, and generate movements. In this thesis, we contribute to the field of movement computing by building machine-learning-based solutions for automatic movement generation. In particular, we focus on using machine learning techniques and motion capture data to create controllable, generative movement models. We also contribute to the field by creating datasets, tools, and libraries that we have developed during our research. We start our research by reviewing the works on building automatic movement generation systems using machine learning techniques and motion capture data. Our review covers background topics such as high-level movement characterization, training data, features representation, machine learning models, and evaluation methods. Building on our literature review, we present WalkNet, an interactive agent walking movement controller based on neural networks. The expressivity of virtual, animated agents plays an essential role in their believability. Therefore, WalkNet integrates controlling the expressive qualities of movement with the goal-oriented behaviour of an animated virtual agent. It allows us to control the generation based on the valence and arousal levels of affect, the movement’s walking direction, and the mover’s movement signature in real-time. Following WalkNet, we look at controlling movement generation using more complex stimuli such as music represented by audio signals (i.e., non-symbolic music). Music-driven dance generation involves a highly non-linear mapping between temporally dense stimuli (i.e., the audio signal) and movements, which renders a more challenging modelling movement problem. To this end, we present GrooveNet, a real-time machine learning model for music-driven dance generation

Animation, Simulation, and Control of Soft Characters using Layered Representations and Simplified Physics-based Methods

Realistic behavior of computer generated characters is key to bringing virtual environments, computer games, and other interactive applications to life. The plausibility of a virtual scene is strongly influenced by the way objects move around and interact with each other. Traditionally, actions are limited to motion capture driven or pre-scripted motion of the characters. Physics enhance the sense of realism: physical simulation is required to make objects act as expected in real life. To make gaming and virtual environments truly immersive,it is crucial to simulate the response of characters to collisions and to produce secondary effects such as skin wrinkling and muscle bulging. Unfortunately, existing techniques cannot generally achieve these effects in real time, do not address the coupled response of a character's skeleton and skin to collisions nor do they support artistic control. In this dissertation, I present interactive algorithms that enable physical simulation of deformable characters with high surface detail and support for intuitive deformation control. I propose a novel unified framework for real-time modeling of soft objects with skeletal deformations and surface deformation due to contact, and their interplay for object surfaces with up to tens of thousands of degrees of freedom.I make use of layered models to reduce computational complexity. I introduce dynamic deformation textures, which map three dimensional deformations in the deformable skin layer to a two dimensional domain for extremely efficient parallel computation of the dynamic elasticity equations and optimized hierarchical collision detection. I also enhance layered models with responsive contact handling, to support the interplay between skeletal motion and surface contact and the resulting two-way coupling effects. Finally, I present dynamic morph targets, which enable intuitive control of dynamic skin deformations at run-time by simply sculpting pose-specific surface shapes. The resulting framework enables real-time and directable simulation of soft articulated characters with frictional contact response, capturing the interplay between skeletal dynamics and complex,non-linear skin deformations

Advances in Human-Robot Interaction

Rapid advances in the field of robotics have made it possible to use robots not just in industrial automation but also in entertainment, rehabilitation, and home service. Since robots will likely affect many aspects of human existence, fundamental questions of human-robot interaction must be formulated and, if at all possible, resolved. Some of these questions are addressed in this collection of papers by leading HRI researchers

Towards an efficient haptic rendering using data-driven modeling

This thesis focuses on the optimisation of haptic rendering of interactions with deformable models. The research demonstrated that data-driven techniques can produce a real-time, accurate and complex simulation experience. Applications include, but not limited to, virtual training, rapid prototyping, virtual presence, and entertainment

Analysis of Railway Signalling Systems to Increase Line and Node Capacity

"Europe is one of the most urbanized continents on the planet: about 75% of its population lives in urban areas” (European Enviroment Agency, 2017). In this urban context, the car is still the widely used way of transport, while public transport manages to capture residual segments of the demand for mobility. However, in a structural framework of obvious concern and criticality for public transport, there is a component of the sector in strong expansion, that is, all rail transports. In addition, the incidence of rail transport is even more significant in large metropolitan systems where daily travel reaches its highest levels of expression. It is known, however, that the supply of transport services is limited by the capacity of the transport system which depends on the physical size of the infrastructure, that is, the capacity of the infrastructure, the number of vehicles, the capacity of the vehicle fleet, the operating time and the traffic regime implemented