In the collections of natural history, mounted skeletons are among the most complex objects. They are composed of hundreds of different bones, tedious to digitize accurately in 3D because many surfaces remain hidden to the scanning device. A group of researchers from Pierre et Marie Curie (Paris 6) and Grenoble Universities teamed up with researchers from the National Museum of Natural History in Paris in order to design and implement a mathematical model of the bone surface deformation through optimization. The goal is to produce a surface triangulation adapted to the underlying surface intrinsic geometric properties from the sole datum of point clouds of skeleton bones. Outlier points will be removed from the data and the remaining inlier points will be labeled according to their membership to a specific bone structure. The results will be validated from the anatomical point of view and will be used to conduct functional morphology analysis. In our approach, each bone reconstruction of a skeleton will be obtained by morphing a generic representative surface of the same equivalence class using a mathematical derivative-based model. The resolution of this problem will lead to a definition of a closed orientable surface and will allow to account for the conservation of specifically labeled components.

We develop an integrated set of gaits and skills for a physics-based simulation of a quadruped. The motion repertoire for our simulated dog includes walk, trot, pace, canter, transverse gallop, rotary gallop, leaps capable of jumping on-and-off platforms and over obstacles, sitting, lying down, standing up, and getting up from a fall. The controllers use a representation based on gait graphs, a dual leg frame model, a flexible spine model, and the extensive use of internal virtual forces applied via the Jacobian transpose. Optimizations are applied to these control abstractions in order to achieve robust gaits and leaps with desired motion styles. The resulting gaits are evaluated for robustness with respect to push disturbances and the traversal of variable terrain. The simulated motions are also compared to motion data captured from a filmed dog.

Abstract Creating and animating subject‐specific anatomical models is traditionally a difficult process involving medical image segmentation, geometric corrections and the manual definition of kinematic parameters. In this paper, we introduce a novel template morphing algorithm that facilitates three‐dimensional modelling and parameterization of skeletons. Target data can be either medical images or surfaces of the whole skeleton. We incorporate prior knowledge about bone shape, the feasible skeleton pose and the morphological variability in the population. This allows for noise reduction, bone separation and the transfer, from the template, of anatomical and kinematical information not present in the input data. Our approach treats both local and global deformations in successive regularization steps: smooth elastic deformations are represented by an as‐rigid‐as‐possible displacement field between the reference and current configuration of the template, whereas global and discontinuous displacements are estimated through a projection onto a statistical shape model and a new joint pose optimization scheme with joint limits.

Abstract This paper presents a real‐time method to animate complex scenes of thousands of trees under a user‐controllable wind load. Firstly, modal analysis is applied to extract the main modes of deformation from the mechanical model of a 3D tree. The novelty of our contribution is to precompute a new basis of the modal stress of the tree under wind load. At runtime, this basis allows to replace the modal projection of the external forces by a direct mapping for any directional wind. We show that this approach can be efficiently implemented on graphics hardware. This modal animation can be simulated at low computation cost even for large scenes containing thousands of trees.

Abstract We present a general method to intuitively create a wide range of locomotion controllers for 3D legged characters. The key of our approach is the assumption that efficient locomotion can exploit the natural vibration modes of the body, where these modes are related to morphological parameters such as the shape, size, mass, and joint stiffness. The vibration modes are computed for a mechanical model of any 3D character with rigid bones, elastic joints, and additional constraints as desired. A small number of vibration modes can be selected with respect to their relevance to locomotion patterns and combined into a compact controller driven by very few parameters. We show that these controllers can be used in dynamic simulations of simple creatures, and for kinematic animations of more complex creatures of a variety of shapes and sizes.

Abstract Films like Shrek, Madagascar, The Chronicles of Narnia and Charlotte's web all have something in common: realistic quadruped animations. While the animation of animals has been popular for a long time, the technical challenges associated with creating highly realistic, computer generated creatures have been receiving increasing attention recently. The entertainment, education and medical industries have increased the demand for simulation of realistic animals in the computer graphics area. In order to achieve this, several challenges need to be overcome: gathering and processing data that embodies the natural motion of an animal – which is made more difficult by the fact that most animals cannot be easily motion‐captured; building accurate kinematic models for animals, with adapted animation skeletons in particular; and developing either kinematic or physically‐based animation methods, either by embedding some a priori knowledge about the way that quadrupeds locomote and/or adopting examples of real motion. In this paper, we present an overview of the common techniques used to date for realistic quadruped animation. This includes an outline of the various ways that realistic quadruped motion can be achieved, through video‐based acquisition, physics based models, inverse kinematics or some combination of the above.

Abstract Due to the growing need for large quantities of human animation data in the entertainment industry, it has become a necessity to compress motion capture sequences in order to ease their storage and transmission. We present a novel, lossy compression method for human motion data that exploits both temporal and spatial coherence. Given one motion, we first approximate the poses manifold using Principal Geodesics Analysis (PGA) in the configuration space of the skeleton. We then search this approximate manifold for poses matching end‐effectors constraints using an iterative minimization algorithm that allows for real‐time, data‐driven inverse kinematics. The compression is achieved by only storing the approximate manifold parametrization along with the end‐effectors and root joint trajectories, also compressed, in the output data. We recover poses using the IK algorithm given the end‐effectors trajectories. Our experimental results show that considerable compression rates can be obtained using our method, with few reconstruction and perceptual errors.

International audience

International audience

This paper examines the influence of head orientation in liptracking. There are two main conclusions: First, lip gesture analysis and head movement correction should be processed independently. Second, the measurement of articulatory parameters may be corrupted by head movement if it is performed directly at the pixel level. We thus propose an innovative technique of liptracking which relies on a active contour model of the lips controlled by articulatory parameters. The 3D model is projected onto the image of a speaking face through a camera model, thus allowing spatial re-orientation of the head. Liptracking is then performed by automatic adjustment of the control parameters, independently of head orientation. The final objective of our study is to apply a pixel-based method to detect head orientation. Nevertheless, we consider that head motion and lip gestures are detected by different processes, whether cognitive (by humans) or computational (by machines). Due to this, we decided to first develop and evaluate orientation-free liptracking through a non video-based head motion detection technique which is here presented.

This paper presents a method for the extraction of articulatory parameters from direct processing of raw images of the lips. After an overview of speechreading and the existing lipreading systems, a set of 23 reference lip shapes phonetically labelled, called visemes, are presented. Our system architecture can be seen as made of three independent parts. First, a new greyscale mouth image is centred and down sampled. Second, this image is projected onto a basis of images computed from the visemes. Then, a multivariate interpolation based on the visemes is applied to predict articulatory parameters from the projection coefficients.