Animation of Human Locomotion Using Sagittal Elevation Angles

This paper presents a data-driven procedural model for the kinematic animation of human walking. The use of data yields realistic looking gait, while the procedural model yields flexibility. We present a new motion data representation, the sagittal elevation angles, and present biomechanical evidence that these angles have a stereotyped pattern across many different walking situations, implying their reusability as a motion data source. We also sketch our algorithm for animating human gait based on sagittal elevation angle data which allows us to generate curved locomotion on uneven terrain with stylistic variation without requiring new datasets

Software Tools for Dynamic and Kinematic Modeling of Human Emotion

Human body modeling has been undertaken in both the fields of biomechanics and computer graphics. Historically, each approach has lacked some of the advantages of the the other. This project further develops one model used for human task studies and computer animation by improving motion realism and facilitating user interaction with the model. Realism is provided by an interface that links a general purpose mechanism simulator with the JACK graphics environment and a prototype human figure with realistic mass and joint properties based on studies in the biomechanics literature. Improved interaction is achieved through software tools which can position several of the figures joints simultaneously. Also, a tool is developed for calculating the mass and inertia properties of an arbitrary polyhedron based on its geometry and an assumption of constant density. Finally, suggestions are offered for future study

Dynamic modelling of articulated figures suitable for the purpose of computer animation

The animation of articulated bodies presents interest in the areas of biomechanics, sports, medicine and the entertainment industry. Traditional motion control methods for these bodies, such as kinematics and rotoscoping are either expensive to use or very laborious. The motion of articulated bodies is complex mostly because of their number of articulations and the diversity of possible motions. This thesis investigates the possibility of using dynamic analysis in order to define the motion of articulated bodies. Dynamic analysis uses physical quantities such as forces, torques and accelerations, to calculate the motion of the body. The method used in this thesis is based upon the inverse Lagrangian dynamics formulation, which, given the accelerations, velocities and positions of each of the articulations of the body, finds the forces or torques that are necessary to generate such motion. Dynamic analysis offers the possibility of generating more realistic motion and also of automating the process of motion control. The Lagrangian formulation was used first in robotics and thus the necessary adaptations for using it in computer animation are presented. An analytical method for the calculation of ground reaction forces is also derived, as these are the most important external forces in the case of humans and the other animals that are of special interest in computer animation. The application of dynamic analysis in bipedal walking is investigated. Two models of increasing complexity are discussed. The issue of motion specification for articulated bodies is also examined. A software environment, Solaris, is described which includes the facility of dynamic and kinematic motion control for articulated bodies. Finally, the advantages and problematics of dynamic analysis with respect to kinematics and other methods are discussed

VCoach: A Customizable Visualization and Analysis System for Video-based Running Coaching

Videos are accessible media for analyzing sports postures and providing feedback to athletes. Existing video-based coaching systems often present feedback on the correctness of poses by augmenting videos with visual markers either manually by a coach or automatically by computing key parameters from poses. However, previewing and augmenting videos limit the analysis and visualization of human poses due to the fixed viewpoints, which confine the observation of captured human movements and cause ambiguity in the augmented feedback. Besides, existing sport-specific systems with embedded bespoke pose attributes can hardly generalize to new attributes; directly overlaying two poses might not clearly visualize the key differences that viewers would like to pursue. To address these issues, we analyze and visualize human pose data with customizable viewpoints and attributes in the context of common biomechanics of running poses, such as joint angles and step distances. Based on existing literature and a formative study, we have designed and implemented a system, VCoach, to provide feedback on running poses for amateurs. VCoach provides automatic low-level comparisons of the running poses between a novice and an expert, and visualizes the pose differences as part-based 3D animations on a human model. Meanwhile, it retains the users' controllability and customizability in high-level functionalities, such as navigating the viewpoint for previewing feedback and defining their own pose attributes through our interface. We conduct a user study to verify our design components and conduct expert interviews to evaluate the usefulness of the system

Automated gait generation based on traditional animation

This thesis describes the development of a tool to assist animators in doing walk cycles. In traditional animation, animators create expressive walk cycles with key poses. The process of generating walk cycles by hand is tedious and repetitive. To help animators, many researchers in computer graphics have worked on automating gait generation. However, almost all of them used methods that eliminate animator defined key poses. Although they produce realistic results, their methods are not suitable for expressive walk cycles that can be found in cartoons. The tool described in this thesis attempts to incorporate practices of traditional animators such as comparison of key poses and the use of arc into the program interface. With this tool, animators can concentrate only on setting key poses, which is the most creative task in animating expressive walk. The gait generation program can produce highly expressive walks like the double bounce walk and the sneak. With automated features of the developed tool, animators can save time and effort when animating expressive walk along a curved path

Simulating Humans: Computer Graphics, Animation, and Control

People are all around us. They inhabit our home, workplace, entertainment, and environment. Their presence and actions are noted or ignored, enjoyed or disdained, analyzed or prescribed. The very ubiquitousness of other people in our lives poses a tantalizing challenge to the computational modeler: people are at once the most common object of interest and yet the most structurally complex. Their everyday movements are amazingly uid yet demanding to reproduce, with actions driven not just mechanically by muscles and bones but also cognitively by beliefs and intentions. Our motor systems manage to learn how to make us move without leaving us the burden or pleasure of knowing how we did it. Likewise we learn how to describe the actions and behaviors of others without consciously struggling with the processes of perception, recognition, and language

Adaptive motion synthesis and motor invariant theory.

Generating natural-looking motion for virtual characters is a challenging research topic. It becomes even harder when adapting synthesized motion to interact with the environment. Current methods are tedious to use, computationally expensive and fail to capture natural looking features. These difficulties seem to suggest that artificial control techniques are inferior to their natural counterparts. Recent advances in biology research point to a new motor control principle: utilizing the natural dynamics. The interaction of body and environment forms some patterns, which work as primary elements for the motion repertoire: Motion Primitives. These elements serve as templates, tweaked by the neural system to satisfy environmental constraints or motion purposes. Complex motions are synthesized by connecting motion primitives together, just like connecting alphabets to form sentences. Based on such ideas, this thesis proposes a new dynamic motion synthesis method. A key contribution is the insight into dynamic reason behind motion primitives: template motions are stable and energy efficient. When synthesizing motions from templates, valuable properties like stability and efficiency should be perfectly preserved. The mathematical formalization of this idea is the Motor Invariant Theory and the preserved properties are motor invariant In the process of conceptualization, newmathematical tools are introduced to the research topic. The Invariant Theory, especially mathematical concepts of equivalence and symmetry, plays a crucial role. Motion adaptation is mathematically modelled as topological conjugacy: a transformation which maintains the topology and results in an analogous system. The Neural Oscillator and Symmetry Preserving Transformations are proposed for their computational efficiency. Even without reference motion data, this approach produces natural looking motion in real-time. Also the new motor invariant theory might shed light on the long time perception problem in biological research

The biomechanics of human locomotion

Includes bibliographical references. The thesis on CD-ROM includes Animate, GaitBib, GaitBook and GaitLab, four quick time movies which focus on the functional understanding of human gait. The CD-ROM is available at the Health Sciences Library

Initiation and control of gait from first principles: a mathematically animated model of the foot

The initiation of bipedal gait is a willed action that causes a body at rest to move. Newton's first principle of motion is applied to experimental footprint data. leading to the premise that the big toe is the source of the body action force that initiates and controls bipedal gait