Automatic Modeling of Animatable Virtual Humans – A Survey Nadia Magnenat-Thalmann, Hyewon Seo, Frederic Cordier MIRALab – University of Geneva {thalmann, seo, cordier}@miralab.unige.ch Abstract 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. This paper studies 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. Keywords Human body modeling, animatable models, automatic methods 1. Introduction Human body modeling and animation have been one of the most difficult tasks encountered by animators. In particular, realistic human body modeling requires an accurate geometric surface throughout the simulation. At this time, a variety of human body modeling methodologies are available, that can be classified into three major categories: creative, reconstructive, and interpolated. Anatomically based modelers, such as Scheepers et al [27], Shen and Thalmann [31] and Wilhelms and Van Gelder [33] fall into the former approach. They observe that the models should mimic actual components of the body and their models consist of multi-layers for simulating individual muscles, bones and tissues. While allowing for an interactive design, they however require considerable user intervention and thus suffer from a relatively slow production time and a lack of efficient control facilities. Lately, much work has been devoted to the reconstructive approach to build 3D geometry of human automatically by capturing existing shape. Some of them rely on stereo [11], structured light [23], or 3D scanners [6]. Some systems use 2D images either from video sequences [13] or from photos [19][15]. While they are effective and visually convincing, one limiting factor of these techniques lies in that they hardly give any control to the user; i.e., it is very difficult to automatically modify resulting models to different shapes as the user intends. The third major category, interpolated modeling, uses sets of example models with an interpolation scheme to construct new models. Because interpolation provides a way to leverage existing models to generate new ones with a high level of control in an interactive time, it has gained growing popularity in various graphical objects including human models. This paper reviews automatic modeling techniques for animatable virtual humans, primarily for real-time applications. We focus our study on body modeling which are readily animatable. Model-based reconstructive methods and interpolated methods are discussed in detail, because anatomical models are more designated to the interactive design. This paper is organized as follows: First we look for methods for shape capture of real people (Section 2). Then we review methods for modeling the variety of human body shapes in Section 3. After studying methods for dynamic shape change as the body moves in Section 4, we continue in Section 5 to the methods for dealing with dressed humans. We conclude the paper in Section 6. 2. Shape capture Since the advent of 3D image capture technology, there has been a great deal of interest in the application of that technology to the measurement of the human body. In the market, there are now available several systems that are optimized either for extracting accurate measurements from parts of the body, or for realistic visualization for use in games, virtual environments and, lately, e-commerce applications [8]. For many years, the goal has been to develop techniques to convert the scanned data into complete, readily animatable models. Apart from solving the classical problems such as the hole filling and noise reduction, the internal skeleton hierarchy should be appropriately estimated in order to make them move. Accordingly, several approaches have been under active development to endow semantic structure to the scan data. Dekker et al [10] have used a series of meaningful anatomical assumptions in order to optimize, clean and segment data from a Hamamatsu whole body range scanner in order to generate quad mesh representations of human bodies and build applications for the clothing industry. Ju and others Proceedings of the Fourth International Conference on 3-D Digital Imaging and Modeling (3DIM’03) 0-7695-1991-1/03 $ 17.00 © 2003 IEEE