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

Production and Playback of Human Figure Motion 3D Virtual Environments

We describe a system for off-line production and real-time playback of motion for articulated human figures in 3D virtual environments. The key notions are (1) the logical storage of full body motion in posture graphs, which provides a simple motion access method for playback, and (2) mapping the motions of higher DOF figures using slaving to provide human models at several levels of detail, both in geometry and articulation, for later playback. We present our system in a context of a simple problem: Animating human figures in a distributed simulation, using DIS protocols for communication the human state information. We also discuss several related techniques for real-time animation of articulated figures in visual simulation

Virtual humans: thirty years of research, what next?

In this paper, we present research results and future challenges in creating realistic and believable Virtual Humans. To realize these modeling goals, real-time realistic representation is essential, but we also need interactive and perceptive Virtual Humans to populate the Virtual Worlds. Three levels of modeling should be considered to create these believable Virtual Humans: 1) realistic appearance modeling, 2) realistic, smooth and flexible motion modeling, and 3) realistic high-level behaviors modeling. At first, the issues of creating virtual humans with better skeleton and realistic deformable bodies are illustrated. To give a level of believable behavior, challenges are laid on generating on the fly flexible motion and complex behaviours of Virtual Humans inside their environments using a realistic perception of the environment. Interactivity and group behaviours are also important parameters to create believable Virtual Humans which have challenges in creating believable relationship between real and virtual humans based on emotion and personality, and simulating realistic and believable behaviors of groups and crowds. Finally, issues in generating realistic virtual clothed and haired people are presente

Interactive techniques for motion deformation of articulated figures using prioritized constraints

Convincingly animating virtual humans has become of great interest in many fields since recent years. In computer games for example, virtual humans often are the main characters. Failing to realistically animate them may wreck all previous efforts made to provide the player with an immersion feeling. At the same time, computer generated movies have become very popular and thus have increased the demand for animation realism. Indeed, virtual humans are now the new stars in movies like Final Fantasy or Shrek, or are even used for special effects in movies like Matrix. In this context, the virtual humans animations not only need to be realistic as for computer games, but really need to be expressive as for real actors. While creating animations from scratch is still widespread, it demands artistics skills and hours if not days to produce few seconds of animation. For these reasons, there has been a growing interest for motion capture: instead of creating a motion, the idea is to reproduce the movements of a live performer. However, motion capture is not perfect and still needs improvements. Indeed, the motion capture process involves complex techniques and equipments. This often results in noisy animations which must be edited. Moreover, it is hard to exactly foresee the final motion. For example, it often happens that the director of a movie decides to change the script. The animators then have to change part or the whole animation. The aim of this thesis is then to provide animators with interactive tools helping them to easily and rapidly modify preexisting animations. We first present our Inverse Kinematics solver used to enforce kinematic constraints at each time of an animation. Afterward, we propose a motion deformation framework offering the user a way to specify prioritized constraints and to edit an initial animation so that it may be used in a new context (characters, environment,etc). Finally, we introduce a semi-automatic algorithm to extract important motion features from motion capture animation which may serve as a first guess for the animators when specifying important characteristics an initial animation should respect

Articulated human tracking and behavioural analysis in video sequences

Recently, there has been a dramatic growth of interest in the observation and tracking of human subjects through video sequences. Arguably, the principal impetus has come from the perceived demand for technological surveillance, however applications in entertainment, intelligent domiciles and medicine are also increasing. This thesis examines human articulated tracking and the classi cation of human movement, rst separately and then as a sequential process. First, this thesis considers the development and training of a 3D model of human body structure and dynamics. To process video sequences, an observation model is also designed with a multi-component likelihood based on edge, silhouette and colour. This is de ned on the articulated limbs, and visible from a single or multiple cameras, each of which may be calibrated from that sequence. Second, for behavioural analysis, we develop a methodology in which actions and activities are described by semantic labels generated from a Movement Cluster Model (MCM). Third, a Hierarchical Partitioned Particle Filter (HPPF) was developed for human tracking that allows multi-level parameter search consistent with the body structure. This tracker relies on the articulated motion prediction provided by the MCM at pose or limb level. Fourth, tracking and movement analysis are integrated to generate a probabilistic activity description with action labels. The implemented algorithms for tracking and behavioural analysis are tested extensively and independently against ground truth on human tracking and surveillance datasets. Dynamic models are shown to predict and generate synthetic motion, while MCM recovers both periodic and non-periodic activities, de ned either on the whole body or at the limb level. Tracking results are comparable with the state of the art, however the integrated behaviour analysis adds to the value of the approach.Overseas Research Students Awards Scheme (ORSAS

Supplementing Frequency Domain Interpolation Methods for Character Animation

The animation of human characters entails difficulties exceeding those met simulating objects, machines or plants. A person's gait is a product of nature affected by mood and physical condition. Small deviations from natural movement are perceived with ease by an unforgiving audience. Motion capture technology is frequently employed to record human movement. Subsequent playback on a skeleton underlying the character being animated conveys many of the subtleties of the original motion. Played-back recordings are of limited value, however, when integration in a virtual environment requires movements beyond those in the motion library, creating a need for the synthesis of new motion from pre-recorded sequences. An existing approach involves interpolation between motions in the frequency domain, with a blending space defined by a triangle network whose vertices represent input motions. It is this branch of character animation which is supplemented by the methods presented in this thesis, with work undertaken in three distinct areas. The first is a streamlined approach to previous work. It provides benefits including an efficiency gain in certain contexts, and a very different perspective on triangle network construction in which they become adjustable and intuitive user-interface devices with an increased flexibility allowing a greater range of motions to be blended than was possible with previous networks. Interpolation-based synthesis can never exhibit the same motion variety as can animation methods based on the playback of rearranged frame sequences. Limitations such as this were addressed by the second phase of work, with the creation of hybrid networks. These novel structures use properties of frequency domain triangle blending networks to seamlessly integrate playback-based animation within them. The third area focussed on was distortion found in both frequency- and time-domain blending. A new technique, single-source harmonic switching, was devised which greatly reduces it, and adds to the benefits of blending in the frequency domain

Exploiting quaternions to support expressive interactive character motion

Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2003.Includes bibliographical references (p. 261-266).A real-time motion engine for interactive synthetic characters, either virtual or physical, needs to allow expressivity and interactivity of motion in order to maintain the illusion of life. Canned animation examples from an animator or motion capture device are expressive, but not very interactive, often leading to repetition. Conversely, numerical procedural techniques such as Inverse Kinematics (IK) tend to be very interactive, but often appear "robotic" and require parameter tweaking by hand. We argue for the use of hybrid example-based learning techniques to incorporate expert knowledge of character motion in the form of animations into an interactive procedural engine. Example-based techniques require appropriate distance metrics, statistical analysis and synthesis primitives, along with the ability to blend examples; furthermore, many machine learning techniques are sensitive to the choice of representation. We show that a quaternion representation of the orientation of a joint affords us computational efficiency along with mathematical robustness, such as avoiding gimbal lock in the Euler angle representation. We show how to use quaternions and their exponential mappings to create distance metrics on character poses, perform simple statistical analysis of joint motion limits and blend multiple poses together. We demonstrate these joint primitives on three techniques which we consider useful for combining animation knowledge with procedural algorithms: 1) pose blending, 2) joint motion statistics and 3) expressive IK. We discuss several projects designed using these primitives and offer insights for programmers building real-time motion engines for expressive interactive characters.by Michael Patrick Johnson.Ph.D