Style-based Motion Synthesis

Representing motions as linear sums of principal components has become a widely accepted animation technique. While powerful, the simplest version of this approach is not particularly well suited to modeling the specific style of an individual whose motion had not yet been recorded when building the database: it would take an expert to adjust the PCA weights to obtain a motion style that is indistinguishable from his. Consequently, when realism is required, the current practice is to perform a full motion capture session each time a new person must be considered. In this paper, we extend the PCA approach so that this requirement can be drastically reduced: for whole classes of cyclic and noncyclic motions such as walking, running or jumping, it is enough to observe the newcomer moving only once at a particular speed or jumping a particular distance using either an optical motion capture system or a simple pair of synchronized video cameras. This one observation is used to compute a set of principal component weights that best approximates the motion and to extrapolate in real-time realistic animations of the same person walking or running at different speeds, and jumping a different distanc

Mahalanobis Motion Generation

Representing motions as linear sums of principal components has become a widely accepted animation technique. While powerful, the simplest version of this approach is not particularly well suited to modeling the specific style of an individual whose motion had not yet been recorded when building the database: It would take an expert to adjust the PCA weights to obtain a motion style that is indistinguishable from his. Consequently, when realism is required, current practice is to perform a full motion capture session each time a new person must be considered. In this paper, we extend the PCA approach so that this requirement can be drastically reduced: For whole classes of motion such as walking or running, it is enough to observe the newcomer moving only once at a particular speed using either an optical motion capture system or a simple pair of synchronized video cameras. This one observation is used to compute a set of principal component weights that best approximates the motion and to extrapolate in real-time realistic animations of the same person walking or running at different speeds

Dynamic Obstacle Clearing for Real-time Character Animation

This paper proposes a novel method to control virtual characters in dynamic environments. A virtual character is animated by a locomotion and jumping engine, enabling production of continuous parameterized motions. At any time during runtime, flat obstacles (e.g. a puddle of water) can be created and placed in front of a character. The method first decides whether the character is able to get around or jump over the obstacle. Then the motion parameters are accordingly modified. The transition from locomotion to jump is performed with an improved motion blending technique. While traditional blending approaches let the user choose the transition time and duration manually, our approach automatically controls transitions between motion patterns whose parameters are not known in advance. In addition, according to the animation context, blending operations are executed during a precise period of time to preserve specific physical properties. This ensures coherent movements over the parameter space of the original input motions. The initial locomotion type and speed are smoothly varied with respect to the required jump type and length. This variation is carefully computed in order to place the take-off foot as close to the created obstacle as possible

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

On-line locomotion synthesis for virtual humans

Ever since the development of Computer Graphics in the industrial and academic worlds in the seventies, public knowledge and expertise have grown in a tremendous way, notably because of the increasing fascination for Computer Animation. This specific field of Computer Graphics gathers numerous techniques, especially for the animation of characters or virtual humans in movies and video games. To create such high-fidelity animations, a particular interest has been dedicated to motion capture, a technology which allows to record the 3D movement of a live performer. The resulting realism motion is convincing. However, this technique offers little control to animators, as the recorded motion can only be played back. Recently, many advances based on motion capture have been published, concerning slight but precise modifications of an original motion or the parameterization of large motion databases. The challenge consists in combining motion realism with an intuitive on-line motion control, while preserving real-time performances. In the first part of this thesis, we would like to add a brick in the wall of motion parameterization techniques based on motion capture, by introducing a generic motion modeling for locomotion and jump activities. For this purpose, we simplify the motion representation using a statistical method in order to facilitate the elaboration of an efficient parametric model. This model is structured in hierarchical levels, allowing an intuitive motion synthesis with high-level parameters. In addition, we present a space and time normalization process to adapt our model to characters of various sizes. In the second part, we integrate this motion modeling in an animation engine, thus allowing for the generation of a continuous stream of motion for virtual humans. We provide two additional tools to improve the flexibility of our engine. Based on the concept of motion anticipation, we first introduce an on-line method for detecting and enforcing foot-ground constraints. Hence, a straight line walking motion can be smoothly modified to a curved one. Secondly, we propose an approach for the automatic and coherent synthesis of transitions from locomotion to jump (and inversely) motions, by taking into account their respective properties. Finally, we consider the interaction of a virtual human with its environment. Given initial and final conditions set on the locomotion speed and foot positions, we propose a method which computes the corresponding trajectory. To illustrate this method, we propose a case study which mirrors as closely as possible the behavior of a human confronted with an obstacle: at any time, obstacles may be interactively created in front of a moving virtual human. Our method computes a trajectory allowing the virtual human to precisely jump over the obstacle in an on-line manner

From motion capture to interactive virtual worlds : towards unconstrained motion-capture algorithms for real-time performance-driven character animation

This dissertation takes performance-driven character animation as a representative application and advances motion capture algorithms and animation methods to meet its high demands. Existing approaches have either coarse resolution and restricted capture volume, require expensive and complex multi-camera systems, or use intrusive suits and controllers. For motion capture, set-up time is reduced using fewer cameras, accuracy is increased despite occlusions and general environments, initialization is automated, and free roaming is enabled by egocentric cameras. For animation, increased robustness enables the use of low-cost sensors input, custom control gesture definition is guided to support novice users, and animation expressiveness is increased. The important contributions are: 1) an analytic and differentiable visibility model for pose optimization under strong occlusions, 2) a volumetric contour model for automatic actor initialization in general scenes, 3) a method to annotate and augment image-pose databases automatically, 4) the utilization of unlabeled examples for character control, and 5) the generalization and disambiguation of cyclical gestures for faithful character animation. In summary, the whole process of human motion capture, processing, and application to animation is advanced. These advances on the state of the art have the potential to improve many interactive applications, within and outside virtual reality.Diese Arbeit befasst sich mit Performance-driven Character Animation, insbesondere werden Motion Capture-Algorithmen entwickelt um den hohen Anforderungen dieser Beispielanwendung gerecht zu werden. Existierende Methoden haben entweder eine geringe Genauigkeit und einen eingeschränkten Aufnahmebereich oder benötigen teure Multi-Kamera-Systeme, oder benutzen störende Controller und spezielle Anzüge. Für Motion Capture wird die Setup-Zeit verkürzt, die Genauigkeit für Verdeckungen und generelle Umgebungen erhöht, die Initialisierung automatisiert, und Bewegungseinschränkung verringert. Für Character Animation wird die Robustheit für ungenaue Sensoren erhöht, Hilfe für benutzerdefinierte Gestendefinition geboten, und die Ausdrucksstärke der Animation verbessert. Die wichtigsten Beiträge sind: 1) ein analytisches und differenzierbares Sichtbarkeitsmodell für Rekonstruktionen unter starken Verdeckungen, 2) ein volumetrisches Konturenmodell für automatische Körpermodellinitialisierung in genereller Umgebung, 3) eine Methode zur automatischen Annotation von Posen und Augmentation von Bildern in großen Datenbanken, 4) das Nutzen von Beispielbewegungen für Character Animation, und 5) die Generalisierung und Übertragung von zyklischen Gesten für genaue Charakteranimation. Es wird der gesamte Prozess erweitert, von Motion Capture bis hin zu Charakteranimation. Die Verbesserungen sind für viele interaktive Anwendungen geeignet, innerhalb und außerhalb von virtueller Realität

From motion capture to interactive virtual worlds : towards unconstrained motion-capture algorithms for real-time performance-driven character animation

This dissertation takes performance-driven character animation as a representative application and advances motion capture algorithms and animation methods to meet its high demands. Existing approaches have either coarse resolution and restricted capture volume, require expensive and complex multi-camera systems, or use intrusive suits and controllers. For motion capture, set-up time is reduced using fewer cameras, accuracy is increased despite occlusions and general environments, initialization is automated, and free roaming is enabled by egocentric cameras. For animation, increased robustness enables the use of low-cost sensors input, custom control gesture definition is guided to support novice users, and animation expressiveness is increased. The important contributions are: 1) an analytic and differentiable visibility model for pose optimization under strong occlusions, 2) a volumetric contour model for automatic actor initialization in general scenes, 3) a method to annotate and augment image-pose databases automatically, 4) the utilization of unlabeled examples for character control, and 5) the generalization and disambiguation of cyclical gestures for faithful character animation. In summary, the whole process of human motion capture, processing, and application to animation is advanced. These advances on the state of the art have the potential to improve many interactive applications, within and outside virtual reality.Diese Arbeit befasst sich mit Performance-driven Character Animation, insbesondere werden Motion Capture-Algorithmen entwickelt um den hohen Anforderungen dieser Beispielanwendung gerecht zu werden. Existierende Methoden haben entweder eine geringe Genauigkeit und einen eingeschränkten Aufnahmebereich oder benötigen teure Multi-Kamera-Systeme, oder benutzen störende Controller und spezielle Anzüge. Für Motion Capture wird die Setup-Zeit verkürzt, die Genauigkeit für Verdeckungen und generelle Umgebungen erhöht, die Initialisierung automatisiert, und Bewegungseinschränkung verringert. Für Character Animation wird die Robustheit für ungenaue Sensoren erhöht, Hilfe für benutzerdefinierte Gestendefinition geboten, und die Ausdrucksstärke der Animation verbessert. Die wichtigsten Beiträge sind: 1) ein analytisches und differenzierbares Sichtbarkeitsmodell für Rekonstruktionen unter starken Verdeckungen, 2) ein volumetrisches Konturenmodell für automatische Körpermodellinitialisierung in genereller Umgebung, 3) eine Methode zur automatischen Annotation von Posen und Augmentation von Bildern in großen Datenbanken, 4) das Nutzen von Beispielbewegungen für Character Animation, und 5) die Generalisierung und Übertragung von zyklischen Gesten für genaue Charakteranimation. Es wird der gesamte Prozess erweitert, von Motion Capture bis hin zu Charakteranimation. Die Verbesserungen sind für viele interaktive Anwendungen geeignet, innerhalb und außerhalb von virtueller Realität

Tracking and modelling motion for biomechanical analysis

This thesis focuses on the problem of determining appropriate skeletal configurations for which a virtual animated character moves to desired positions as smoothly, rapidly, and as accurately as possible. During the last decades, several methods and techniques, sophisticated or heuristic, have been presented to produce smooth and natural solutions to the Inverse Kinematics (IK) problem. However, many of the currently available methods suffer from high computational cost and production of unrealistic poses. In this study, a novel heuristic method, called Forward And Backward Reaching Inverse Kinematics (FABRIK), is proposed, which returns visually natural poses in real-time, equally comparable with highly sophisticated approaches. It is capable of supporting constraints for most of the known joint types and it can be extended to solve problems with multiple end effectors, multiple targets and closed loops. FABRIK was compared against the most popular IK approaches and evaluated in terms of its robustness and performance limitations. This thesis also includes a robust methodology for marker prediction under multiple marker occlusion for extended time periods, in order to drive real-time centre of rotation (CoR) estimations. Inferred information from neighbouring markers has been utilised, assuming that the inter-marker distances remain constant over time. This is the first time where the useful information about the missing markers positions which are partially visible to a single camera is deployed. Experiments demonstrate that the proposed methodology can effectively track the occluded markers with high accuracy, even if the occlusion persists for extended periods of time, recovering in real-time good estimates of the true joint positions. In addition, the predicted positions of the joints were further improved by employing FABRIK to relocate their positions and ensure a fixed bone length over time. Our methodology is tested against some of the most popular methods for marker prediction and the results confirm that our approach outperforms these methods in estimating both marker and CoR positions. Finally, an efficient model for real-time hand tracking and reconstruction that requires a minimum number of available markers, one on each finger, is presented. The proposed hand model is highly constrained with joint rotational and orientational constraints, restricting the fingers and palm movements to an appropriate feasible set. FABRIK is then incorporated to estimate the remaining joint positions and to fit them to the hand model. Physiological constraints, such as inertia, abduction, flexion etc, are also incorporated to correct the final hand posture. A mesh deformation algorithm is then applied to visualise the movements of the underlying hand skeleton for comparison with the true hand poses. The mathematical framework used for describing and implementing the techniques discussed within this thesis is Conformal Geometric Algebra (CGA)

Dynamic Time Warp Based Framespace Interpolation For Motion Editing

Motion capture (MOCAP) data clips can be visualized as a sequence of densely spaced curves, defining the joint angles of the articulated figure, over a specified period of time. Current research has focussed on frequency and time domain techniques to edit these curves, preserving the original qualities of the motion yet making it reusable in different spatio-temporal situations. We refine Guo et. al.'s[6] framespace interpolation algorithm which abstracts motion sequences as 1D signals, and interpolates between them to create higher dimension signals. Our method is more suitable for (though not limited to) editing densely spaced MOCAP data, than the existing algorithm. It achieves consistent motion transition through motion-state based dynamic warping of framespaces and automatic transition timing via framespace frequency interpolation