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

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

Exploiting temporal stability and low-rank structure for motion capture data refinement

Inspired by the development of the matrix completion theories and algorithms, a low-rank based motion capture (mocap) data refinement method has been developed, which has achieved encouraging results. However, it does not guarantee a stable outcome if we only consider the low-rank property of the motion data. To solve this problem, we propose to exploit the temporal stability of human motion and convert the mocap data refinement problem into a robust matrix completion problem, where both the low-rank structure and temporal stability properties of the mocap data as well as the noise effect are considered. An efficient optimization method derived from the augmented Lagrange multiplier algorithm is presented to solve the proposed model. Besides, a trust data detection method is also introduced to improve the degree of automation for processing the entire set of the data and boost the performance. Extensive experiments and comparisons with other methods demonstrate the effectiveness of our approaches on both predicting missing data and de-noising. © 2014 Elsevier Inc. All rights reserved

Motion Pattern Encapsulation for Data-Driven Constraint-Based Motion Editing

The growth of motion capture systems have contributed to the proliferation of human motion database, mainly because human motion is important in many applications, ranging from games entertainment and films to sports and medicine. However, the captured motions normally attend specific needs. As an effort for adapting and reusing captured human motions in new tasks and environments and improving the animator’s work, we present and discuss a new data-driven constraint-based animation system for interactive human motion editing. This method offers the compelling advantage that it provides faster deformations and more natural-looking motion results compared to goal-directed constraint-based methods found in the literature

M.-P. Cani, J. O’Brien (Editors) Robust Kinematic Constraint Detection for Motion Data

Motion capture data is now widely available to create realistic character animation. However, it is difficult to reuse without any additional information. For this reason, annotating motion data with kinematic constraints is a clever step to ease further operations such as blending or motion editing. Unfortunately, prior automatic methods prove to be unreliable for noisy data and/or lack genericity. In this paper, we present a method for detecting kinematic constraints for motion data. It detects when an object (or an end-effector) is stationary in space or is rotating around an axis or a point. Our method is fast, generic and may be used on any kind of objects in the scene. Furthermore, it is robust to highly noisy data as we detect and reject aberrant data by using a least median of squares (LMedS) method. We demonstrate the accuracy of our method in various motion editing contexts. Categories and Subject Descriptors (according to ACM CCS): I.3.7 [Computer Graphics]: Three-Dimensiona

Interactive motion deformation with prioritized constraints

In this paper, we present an interactive motion deformation method to modify animations so that they satisfy a set of prioritized constraints. Our approach successfully handles the problem of retargeting and adjusting a motion, as well as adding significant changes to preexisting animations. We introduce the concept of prioritized constraints for motion editing by exploiting an arbitrary large number of priority-layers. Each frame is individually and smoothly adjusted to enforce a set of prioritized constraints. The iterative construction of the solution channels the convergence through intermediate solutions, enforcing the highest prioritized constraints first. In addition, we propose a new, simple formulation to control the position of the center of mass so that the resulting motions are physically plausible. Finally, we demonstrate that our method can address a wide range of motion editing problems. [All rights reserved Elsevier