Search

This article presents a new approach for Fourier-based modeling of bone anatomies for compression and smoothing. By treating the bone surface as a level set of a 31) scalar field, we can model topologically complex models such as bones. In particular, we experiment with five different alternatives, and prove that 31) scalar field which allows monotonous continuity around the boundary can be a good choice for volumetric description of the surface. This allows avoiding Gibbs phenomena which previous volume-based methods have suffered from, returning better results in compression and smoothing than other scalar fields. We demonstrate the efficacy of the proposed method by showing results with various bone data.

In this work, we record a dancer's rhythmic movement with background music. The captured motion sequences are then segmented into dozens of motion clips, to construct a motion database consisting of sets of labeled motion clips. Many of these motion clips contain short and rapid transition from one main dancing motion to another, which causes unnatural, awkward movements when they are connected in different orders than the original sequence. In this paper, we describe our approach for automatically detecting the transition parts in the segmented motion clips. For each motion clip, we model the motion data using the Gaussian mixture model (GMM) and use the resulting distribution cluster map to improve the efficiency and convergence of the clustering, principal component analysis (PCA) has been applied to the motion data prior to performing GMM. Experiments and comparative analysis show that this PCA-based GMM method effectively performs transition detection on the segmented motion clips.

We present our framework that efficiently synchronizes dancing motion of a virtual character according to music input. Two modules have been developed to achieve this. A music server analyzes audio input on the fly and extracts information on music such as tempo, time signature, and beat time. A motion client chooses and displays motion clips according to the music information, by time-warping and synchronizing the start time of motion clips with the music beat time. As a preprocessing step, we construct a database of motion clips using captured dancing motion of a dancer. A PCA-based method is presented to easily identify transiting parts from each motion clip.

Although graphical human modeling has been a long sought subject in computer graphics, when it comes to dealing with real-time applications, it raises a number of unique requirements for both CG artists and researchers. For example, for a real-time performance it is highly desirable to lighten the geometry and optimize the runtime animation of characters wherever possible. An important need in such systems is to assist the CG artists in seamlessly transforming their modeling work from CG packages to the real-time application, without limiting their expressivity. In this paper we describe techniques by which dressed human characters are modeled, loaded into VR scenes, and simulated in real-time. In doing so, we point out challenging issues and solutions that such tasks imply at each phase of modeling and simulation. In particular, we turn our attention to what we consider as key technical components: body and clothes. Case studies show that our modelers successfully meet the need of real-time requirements over a wide variety of scenarios.

Summary form only given. Appropriate combinations of statistical and geometric methods permit modeling and estimation of complex objects. This paper investigates such combinations in the modeling of human body models in computer graphics. By concentrating on such a particular class of objects, we show how example based techniques together with interpolation ones can exploit existing data and knowledge about body shape and size modelling. Graphical modeling of human bodies obviously has applications in the entertainment industry for character animation and simulations involving people. Other applications range from virtual reality to ergonomic and manufacturing studies.

Highly realistic virtual human models are rapidly becoming commonplace in computer graphics. These models, often represented by complex shape and requiring labor-intensive process, challenge the problem of automatic modeling. We study the problem and solutions to automatic modeling of animatable virtual humans. Methods for capturing the shape of real people, parameterization techniques for modeling static shape (the variety of human body shapes) and dynamic shape (how the body shape changes as it moves) of virtual humans are classified, summarized and compared. Finally, methods for clothed virtual humans are reviewed.