CAIAS: camera agent based on intelligent action spotting for real-time participatory animation in virtual stage

Nowadays, it becomes possible to show a live virtual stage application allowing a human's real time participation by motion capture. The big problem in participatory animation is figuring out where to place the camera and in what direction to point it to provide an interesting feedback. In participatory animation such as live stage performance or television show, animation is not specified in the form of giving commands but by a real human's action. Unlike filming, pre- and post-editing is not allowed. Therefore, real time decisions on the visualizing region should be made for camera placement. There have recently been several works on automatic camera control, but none of them is applicable for improvised virtual stage application because they lack the ability to find a situation in real time. The paper addresses the issues and a method for automatic determination of camera placement to visualize live virtual stage animation. Our approach is spotting an actor's action in real time by choosing a necessary level among multiple levels of perception and analysis

On-line locomotion synthesis for virtual humans

Pascal Glardon

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.

EPFL2006

Real-time animation of realistic virtual humans

Amaury Aubel, Daniel Thalmann

The authors have been working on simulating virtual humans for several years. Until recently, these constructs could not act in real time. Today, however, many applications need to simulate in real time virtual humans that look realistic. They have invested considerable effort in developing and integrating several modules into a system capable of animating humans in real-time situations. This includes interactive modules for building realistic individuals and a texture-fitting method suitable for all parts of the head and body. Animating the body, including the hands and their deformations, is the key aspect of the system; to their knowledge, no competing system integrates all these functions. They also included facial animation, as demonstrated below with virtual tennis players. They have developed a single system containing all the modules needed for simulating real-time virtual humans in distant virtual environments (VEs). The system lets one rapidly clone any individual and animate the clone in various contexts. People cannot mistake virtual humans for real ones, but they think them recognizable and realistic

IEEE1998

Construction of animation models out of captured data

Daniel Thalmann

This article describes a method of constructing parametric models out of captured motion and skeleton data. Casting the problem as scattered data interpolation, our work is based on a multi-step approximation for the interpolation function with motion data compressed by principal component analysis. This leads to smaller storage and faster computation than those of previous approaches based on classical methods of exact interpolation. As a result, motion models can be constructed out of a rich set of example data, but can be used for real-time applications. We demonstrate a motion model controllable by attributes including those invariant for each individual, such as age, gender, height and weight. A parametric skeleton model is also constructed and demonstrated

IEEE2002

On-line locomotion synthesis for virtual humans

Pascal Glardon

EPFL2006