A body and garment creation method for an Internet based virtual fitting room. Dimitris Protopsaltou, Christiane Luible, Marlene Arevalo, Nadia Magnenat-Thalmann MIRALab CUI, University of Geneva, CH-1211, Switzerland {protopsaltou, luible, arevalo, thalmann}@miralab.unige.ch Abstract In this paper we present a new methodology for producing 3D clothes, with realistic behavior, providing users with an apposite feel for the garment’s details. The 3D garments that are produced, using our methodology, originate from 2D CAD patterns of real garments and correspond to the regular sizes that can be found on a shop floor. Our aim is to build a compelling, interactive and highly realistic virtual shop, where visitors can choose between many different types of garments designs and proceed to simulate these garments on virtually animated bodies. By merging the approach often used by the fashion industry, in designing clothes, and our own methodology for creating dressed virtual humans, we present a new technique providing troublefree and straightforward garment visualization. The entire process starts from the creation of virtual bodies (either male or female), using standard measurements, which form the basis for garment modeling. Using splines, the 2D garment patterns are created and then seemed together around a virtual human body, providing the initial shape. A simulation is made using the seemed garment by applying physical parameters based on real fabric properties. Once the garment has been created, a real time platform, which has been embedded inside a web browser, is used as an interface to the Internet. We extend the web interface to add interactivity and the ability to dynamically change textures, clothes, body measurements, animation sequences and certain features of the virtual environment. The whole methodology does not aim to build only a virtual dressing room, where customers can view garments fitted onto their own virtual bodies but to visualize made-to-measure clothes, animate them, visualize the cloth behavior and to add interactivity. The entire Virtual Try-On experience is a process of targeting the clientele, designing the clothing collection, dressing the virtual models and then using the web as a virtual shop floor. Keywords: Virtual Try On, 3D clothes, physical behavior, generic bodies 1. Introduction The Internet has emerged as a compelling channel for sale of apparel. Online apparel sales exceeded $1 billion in 1999 and are expected to skyrocket to over $22 billion by 2004 (Forrester Research) [1]. While a significant number of apparel sold over the Internet still this number only represents less than 1% of all apparel sold in the United States and significantly lags Internet penetration in other consumer goods markets (e.g. books and music). A number of recent studies identified the causes for consumer hesitancy. Online shoppers were reluctant to purchase apparel online in 1999 because they could not try on the items. Furthermore of particular note is the consumer’s overwhelming concern with fit and correct sizing, concerns with having to return garments and the inability to fully evaluate garment (quality, details, etc.) [2]. Consumers that purchase apparel online today base their purchase and size-selection decisions mostly on 2D photos of garments and sizing charts. Recognizing the insufficiency of this customer experience, e-tailers have begun to implement improved functionalities on their sites. Recently introduced capabilities allow the customer to view items together, such as a blouse and a skirt, enabling the mix and match of color/texture combinations, and zoom technology, to give the customer a feel for garment details. LandsEnd.com [3] uses My Virtual Model, which provides a virtual mannequin, adjusted to the shopper's proportions. In the same manner, Nordstrom [4] is using 3D technology from California based 3Dshopping.com, which offers 360 degree viewing, enabling complete rotation of the apparel item. Even with these improvements in product presentation, a number of things can go wrong when the consumer pulls the apparel item out of the box. Although there are a number of solutions available, the problem of a realistic “Virtual mirror” still remains one of the main impediments. The most common problems include poor fit, bad drape, or unpleasant feel while wearing the item, or surprise as to the color of the garment. Customer dissatisfaction in any of these areas drives returns, a costly occurrence for e-tailers, and creates lost customer loyalty, an even more costly proposition. Our work proposes an implementation of a simple and fast cloth simulation system that will add to the Virtual Fitting Room the feature of realistic cloth behaviour something that is missing today from the existing Virtual Try On (VTO) solutions in the market. Macy's Passport 99 Fashion Show [5] is one of the most high quality VTO show room that has been created so far. The primary benefit of Macy’s VTO was to introduce dressed bodies animated in real time on the web. Although the user interactivity has been of primary focus, the actual content lacks of realism. The content is highly optimized and although it is optimal for web application, real cloth behavior is not visible. Besides realism, modern applications require cloth simulation to accommodate modern design and visualization processes for which interactivity and real-time rendering are the key features. We propose an adaptation of Macy’s approach to web visualization that provides a decent cross-platform and real-time rendering solution. However this defines major constraints for the underlying simulation methods that should provide high-quality results in very time-constrained situations, and therefore with the minimal required computation. We additionally propose a scheme that brings to the cloth exact fit with the virtual body and physical behavior to fully evaluate the garment. Our work uses a practical implementation of a simple and fast cloth simulation system based on implicit integration [6]. Along the evolution of cloth simulation techniques, focus was primarily aimed to address realism through the accurate reproduction of the mechanical features of fabric materials. The early models, developed a decade ago, had to accommodate very limited computational power and display device, and therefore were geometrical models that were only meant to reproduce the geometrical features of deforming cloth [7]. Then, real mechanical simulation took over, with accurate cloth models simulating the main mechanical properties of fabric. While some models, mostly intended for computer graphics, aimed to simulate complex garments used for dressing virtual characters [8, 9, 10], other studies focused on the accurate reproduction of mechanical behavior, using particle systems [11] [12] or finite elements [13]. Despite all these developments, all these techniques remain dependent on high computational requirements, limiting their application along the new trends toward highly interactive and real-time applications brought by the highly spreading multimedia technologies. While highly accurate methods such as finite elements are not suitable for such applications, developments are now focusing toward approximate models, that can render, using minimal computation, approximate, but realistic results in a very robust way. This paper is composed of two main sections. The first section is a description of the research methodology we used to develop the complete chain of processes for the making of bodies and clothes for a Virtual Fitting Room. The second section is a case study presenting the Virtual Try On developed by MIRALab. 2. Research Methodology 2.1 Generic Bodies Approach With virtual bodies we consider mainly two issues. The first issue is that bodies should correspond to real human body shapes, in order for a user to relate his own body with the virtual body on the screen. The second issue is that virtual bodies should have an appropriate 3D representation for the purpose of cloth simulation and animation. The first phase of our methodology is based entirely on the generation of human body models that are immediately animatable by the modification of an existing reference generic model. This tends to be popular due to the expenses of recovering 3D geometry. Based on adding details or features to an existing generic model, such approach concerns mainly the individualized shape and visual realism using high quality textures. We propose the creation of five generic bodies, for each sex. Every single generic body corresponds to a different standard size: Extra Small, Small, Medium, Large, Extra Large (plus top model shape). However the definition of body shape is dependent on many factors, not just simply the standard sizes. It is a complex application dependent task. General anthropometric classifications (somatotyping) are based on specific sets of measurements with specialised instruments (the ordinary tape being just one of them). Many of these measurements relate to the physical identification of anatomical landmark. Existing descriptions of body shapes in the specific application domain (garment design and fitting) are predominantly qualitative (based on the perception of a human body from experts, e.g. fashion designers, or tailors), or quantitative, based on empirical relationships between body shapes – patterns (basic blocks) and garment drape. The primary data used for the character modeling of the generic bodies were collected from sizing surveys results prepared by the Hohenstein Institute [14]. Figure 1 – Reference generic body The reference generic model (Figure 1) is sliced into a set of contours with each contour corresponding to the set of the measurements as described in the table below (Table 1). To generate a body shape according to the sizes specified, we warp each contour to fit the given measurement and then warp the mesh to interpolate the warped contours. In our approach we take into account only the primary measurements, however manipulation of the secondary body measurements can be facilitated following the same methodology described above. Female Standard Body Sizes 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 Primary Measurements Height Bust girth Under-bust girth Waist girth Hip girth Inside leg length Arm length Neck-base girth Secondary Measurements Outside leg length Back waist length Back width Shoulder slope Shoulder length Front waist length Girth 8cm below waist Waist to Hips Thigh girth Head girth Upper arm length Upper arm girth Wrist girth Neck shoulder point Knee height XS/34 S/36 M/38 L/40 XL/42 168 80 71 65 90 78.3 59.6 34.8 168 84 74 68 94 78.3 59.8 35.4 168 88 77 72 97 78.1 60 36 168 92 80 76 100 77.9 60.2 36.6 168 96 84 80 103 77.7 60.4 37.2 106 41.4 33.5 72 12 41.9 81 21 52 55.4 34.8 26.2 15 25.5 45 106 41.4 34.5 74 12.1 42.8 84 21 53.8 55.6 35 26.8 15.4 26.5 45 106 41.6 35.5 76 12.2 43.7 88 21 55.6 55.8 35.2 28 15.8 27.5 45 106 41.8 36.5 78 12.3 44.6 92 21 57.4 56 35.4 29.2 16.2 28.5 45 106 42 37.5 80 12.4 45.5 96 21 59.2 56.2 35.6 34 16.6 29.5 45 Table 1 – Body Measurements of standard female bodies [14] Figure 3 – Overview of the standard female (left) /male (right) bodies modeled according to sizes The standard male bodies are created using the same methodology as in the case of the female bodies (Figure 3). 2.2 Animation of Generic Bodies Human Motion Capture [15] techniques necessitate strong competences in Virtual Human modelling and animation as well as thorough knowledge of hardware and software pipelines to transform the raw data measured by the hardware into parameters suited for virtual models (e.g. anatomical angles). We used Optical Motion Capture based on markers [16,17]. The typical pipeline production for optical motion capture begins with camera volume calibration, where the relation between all the cameras is computed using recording of dedicated calibration props (assuming the volume set-up [where the cameras are properly aimed at the captured volume] has already been achieved). Then the subject, wearing optical markers (e.g. spheres of 25mm diameter for body capture), is recorded in a static posture so that the operator can manually label all the markers. The operator gives/selects names for each marker in this static pose, usually using anatomically relevant labels (e.g. LKNE for the left knee marker). The information gathered at this stage will be used by the system to label the trajectories automatically during post-processing of dynamic movements. Figure 4 – Technical skeleton The post-processing of motion sequences primarily involves the following two stages: trajectory reconstruction and labelling of markers/trajectories. Once those two steps have been completed, it is possible to visualize the technical skeleton (Figure 4) obtained by drawing segments between the marker positions. From this information the subject skeleton and its animation are derived [18]. It is relatively easy to construct the subject skeleton (or its approximation) from the markers. However, the problem becomes much more complex when considering the body meshes and its deformation parameters. Skin deformation (or skinning) is based on three inter dependant ingredients. First the skeleton topology and geometry, second the mesh or surface of the body, and third the deformation’s own parameters (very often consisting of vertex-level ratios describing the scope of deformation with relation to joints). Good skinning results are achieved by a careful design of these three components, where positions of joints inside the body surface envelope and attachments ratios are very important issues. 2.3 Cloth Simulation and Animation For the simulation of clothes we use MIRACloth as the 3D garment simulator that was developed by the University of Geneva. This engine includes the modules of mechanical model, collision engine, rendering and animation. The algorithms have been integrated in a 3D design framework allowing the management of complex garment objects in interaction with animated virtual characters[19]. This integration has been carried out in the form of a 3DStudio Max plugin (Figure 5). The cloth simulation process has two stages: 1. The garment assembly stage, where the patterns are pulled together and seamed around the body. This is a draping problem involving to obtain a rest position of the garment as quickly as possible. Once the 2D patterns have been placed around the body, a mechanical simulation is invoked, forcing the patterns to approach along the seaming lines. As a result the patterns are attached and seamed on the borders as specified and attain a shape influenced by the form of the body. Thus the garment is constructed around the body (Figure 5). The seaming process relies on a simplified mechanical simulation, where the seam elastics pull the matching pattern borders together. Rather than trying to simulate the exact behavior of fabric, the simplified model optimizes seaming speed using parameters adapted for that purpose, that is to say no gravity, no friction, etc.[20] 2. The garment animation stage, where the motion of the garment is computed as the body is animated. The dynamical motion of the cloth is important here. Figure 5 – 3D simulation of cloth The mechanical parameters of the actual fabric are set, as well as gravity, in order to put the cloth into actual mechanical conditions. Animation of a garment here pertains to its movements along with the virtual body. This is accomplished with collision response and friction with the body surface. At this stage the mechanical parameters are set and tuned with visual feed back. The setting of the parameters may be different from what was used during the process of seaming and construction garments. The mechanical simulation then gives the animation of the garment on a virtual body. The animation parameters, and particularly the mechanical simulation parameters, are adjusted through the parameters panel. It features two categories: environment (global parameters) and object (local parameters). On one hand, among the global simulation parameters, we will find gravity and finally collision distance and detection modes. On the other hand, the local parameters include elasticity, surface density, bending rigidity, friction values, Poisson coefficient, as well as viscosity and non-linear elasticity values, which are the mechanical properties of objects. At this stage we aim to quantify precisely the mechanical parameters that are relevant for the perceptual quality of cloth animation for simulated cloth. Starting from the measured parameters, additional parameters (viscosity, plasticity, non-linearity) are also investigated in order to match the simulated deformations with the real values (Table2,3). The experiments involve a 40x40 cm fabric square maintained by the two corners opposite to the attachment line, and distant by 5 cm from the line (the edge length), giving an initial curved loop shape to the fabric. The validation of the experiments was to perform the constrained fall tests and to compare them to reality using two criteria: the time taken for the fabric to reach vertical position in its initial motion, and the damping of the residual motion. [20] PARAMETERS ELASTICITY Weft elasticity Warp elasticity Shear G Weft bending Warp bending VISCOSITY Weft elasticity Warp elasticity Shear G Weft bending Warp bending DENSITY Linen Cotton Tencel 50 N.m-1 50 N.m-1 55 N.m-1 208.1 10-6 N.m 153.9 10-6 N.m 16.67 N.m-1 16.67 N.m-1 60 N.m-1 10.5 10-6 N.m 6.7 10-6 N.m 25 N.m-1 25 N.m-1 86 N.m-1 25 10-6 N.m 14.8 10-6 N.m 50 10-2 N.m-1.s 50 10-2 N.m-1.s 55 10-2 N.m-1.s 208.1 10-6 N.m.s 153.9 10-6 N.m.s 310 10-3 Kg.m-2 16.67 10-2 N.m-1.s 16.67 10-2 N.m-1.s 60 10-2 N.m-1.s 10.5 10-6 N.m.s 6.7 10-6 N.m.s 310 10-3 Kg.m-2 25 10-2 N.m-1.s 25 10-2 N.m-1.s 86 N.m-1 25 10-6 N.m.s 14.8 10-6 N.m.s 327 10-3 Kg.m-2 Table 2 – Example of fabric parameters1 PARAMETERS 10 m.s-2 GRAVITY AERODYNAMIC VISCOSITY ISOTROPIC (Damping) NORMAL (Flowing) PLASTICITY (f/h) 0.1 N.m-3.s 1 N.m-3.s 1 102 m-1 f = 10 m-1 et h = 0.1 Table 3– External parameters2 Figure 6 –Example of fabric parameters: Linen/Cotton/Tencel The effects of additional parameters (viscosity, plasticity, non-linearity) are further investigated through simulation and perceptual assessment. Finally, complete garments are simulated with the cloth simulation system that integrate the accurate model found relevant and defined from the previous study. 1 -1 Metric elasticity: measurement of the fabric elongation elasticity (N.m ) –Weft and Warp elasticity: elasticity along the Weft and Warp directions –Shear elasticity: elasticity for a shearing deformation between weft and warp directions Bending elasticity: measurement of the fabric bending elasticity (N.m) –Weft and Warp bending: bending along the Weft and Warp directions Viscosity parameters: defined for each elastic parameter -2 Density: mass per surface unit of the fabric (Kg.m ) -2 -2 2 Gravity: nominal acceleration of objects left at rest (9.81 m.s > ~10 m.s ) Aerodynamic viscosity: aerodynamic force exerted on a fabric per surface unit and per velocity unit between the fabric speed and the air speed: -3 -3 –Normal (Flowing: N.m .s) and Isotropic (Damping: N.m .s) components relative to the orientation of the fabric surface 2.4 Web Interface and User Interactivity There is a considerable number of 3D technologies that can be used for the Virtual Fitting Room implementation. Of all the available technologies, VRML (Virtual Reality Modeling Language) [21] is the most established and widely used (ISO standard). Its latest version, VRML97 supports animation and advanced interaction. We used Shout3D [22] as a 3D player/viewer that is implemented using Java taking as input VRML exports from the cloth simulator. The integrated solution is a cross-platform application/viewer accessible by nearly all web browsers. Such application/viewers provide extensibility via APIs, which means that additional desired features can be programmatically added in them. Shout3D is, at bottom, a Java class library. The methods of that library constitute the Shout3D Application Programming Interface (API). We went further and extended this class library to create a new class with new methods. The primary means of utilizing the API is through direct Java programming. We extended the basic Shout3D Applet and Panel classes to create a new class that implement interactivity using the methods in the API. The methods that extend the basic class library aim to control mainly the user interaction with the 3D viewer. That involves input when the user requires changing the cloth on the animated body, body size, background images and scene rotation. This approach is suitable for commercial-quality work that will run reliably on all platforms. It is also possible to use JavaScript to call the methods in the API. The latter approach, while convenient for testing ideas, will not generally be satisfactory for commercial work and will not be functional on all platforms. The Virtual Try On is composed mainly of two web pages, where one contains the 3D viewer and the other the cloth catalogue. The 3D viewer (MIRALab Generic Viewer) after initialization loads the default 3D scene where the dressed models will appear. The generic viewer is an extended version of the basic Shout3D applet. Most interactivity programming is implemented in an extended Panel class. The extended class can implement the DeviceObserver interface to handle mouse and keyboard events from the user. These events are handled in a method named onDeviceInput(). The extended Shout3DPanel class can also make use of the render loop through the RenderObserver interface. This interface consists of the onPreRender() and onPostRender() methods, which are automatically called immediately before or after each render cycle. Initialization duties, such as obtaining references to objects in the scene, are handled by overriding the customInitialize() method of the Shout3DPanel class. The default scene loaded initially is composed of an empty VRML Transform Node namely “emptymodel” that will act as the container where the dressed bodies will load. To implement such interactivity we control the values of class objects that represent nodes in the 3D scene graph. For example, a visitor can manipulate a geometric model only if the panel class has access to the Transform node controlling that geometry. The panel class must therefore create a Transform class object reference variable, and must obtain a reference to place in that variable. Once the reference is obtained, the fields of the Transform node can be changed by means of the reference. The primary means of obtaining such a reference is the change_model() extended method of the miralab_generic class. This method takes the DEF name “model” of the desired node in the VRML scene file as an argument, and returns a reference to the Java class object. With most (but not all) browsers, JavaScript in an HTML page can be used to call methods in the Shout3D API and therefore implement interactivity and procedural animation without writing and compiling extended Shout3DApplet and Shout3DPanel classes. In order to obtain references to objects in the scene, we used the standard change_model() method of the miralab_generic class. This method necessarily requires a reference to the miralab_generic object. Apart from the 3D viewer an important part of the Virtual Try On is the catalogue of the different clothes. We use one of the new features introduced in Microsoft® Internet Explorer 5.5, that is Dynamic HTML (DHTML) behaviors. DHTML behaviors are components that encapsulate specific functionality or behavior on a page. When applied to a standard HTML element on a page, a behavior enhances that element's default behavior. As encapsulated components, behaviors provide easy separation of script from content. This not only makes it easy to reuse code across multiple pages, but also contributes to the improved manageability of the page. The MPC behavior is used to add both the multipage container and the individual page tabs. We use the MPC behavior to create two clothes catalogues (male & female) as shown in the figure 7. Individual page tabs implemented with DHTML help significantly to download a lightweight web page. Figure 7 –The online cloth catalogue implemented with DHTML MPC behavior 3. Case Study – MIRALab’s Virtual Try On 3.1 Preparation of generic bodies The generic model is composed of an H-Anim LoA 2 [23] skeleton hierarchy and a skin mesh. The skin surface is a combination of a Poser character and body models created at the University of Geneva. A proper skin attachment was essential for the skeletal deformation. The attachment is considered as assigning for each vertex of the mesh its affecting bones and corresponding weights. To say that a vertex is "weighted" with respect to a bone means that the vertex will move as the bone is rotated in order to stay aligned with it. At 100 percent weighting, for instance, the vertex follows the bone rigidly. This method combines for each vertex the transformation matrix of the bones in accordance to their weight. Once the skin is properly attached to the skeleton, transformation of the bone automatically derives transformation of the skin mesh [24]. To animate the virtual bodies we used Optical Motion Capture (VICON system at the University of Geneva). To obtain a realistic animation sequence, we hired two professional fashion models (Guido Frauenrath & Sarah Stinson) to simulate a catwalk (Figure 6). The captured animation from the models was applied to the HAnim skeleton to obtain the animated generic body. Figure 8 – Motion Tracking with VICON(left) and H-ANIM skeleton (right) 3.2 Cloth creation and simulation Garments are designed using the traditional 2D pattern approach. We use the Modaris software [25] package to create the patterns. The functionality of the software allows us to simulate the approach of a traditional cloth designer (Figure 9). Figure 9 – 2D patterns creation import in CAD software The patterns then are discretized into a triangular mesh. Following that we place the planar patterns automatically around the body with the use of reference lines (Figure 10). These 2D patterns are constructed and imported in the MIRACloth garment simulator. Figure 10 – 2D patterns creation and positioning around generic body We simulated three different types of clothing for the female bodies (skirt, pullover and dress) each one applied with different fabric properties. • The skirt and the pullover was simulated with the cotton properties (Section 2.3) and • The dress with the tencel properties (Section 2.3) (For the male bodies we applied the same methodology) Since the final models must be optimized for usage on the Internet, each garment was composed of only 1000 polygons. A second step was performed to decrease the weight of the textures, in order not to overload the video memory during the real time visualization on the web, keeping sizes to 512x512 pixels. The final output was exported in VRML. 3DSMax like all 3D animation packages, offers spline interpolation. To approximate the smooth curvature and subtle speed changes of spline interpolated function curves, the 3Dsmax VRML exporter provides a sampling mechanism for linear key frame animation. The greater the number of frame samples, the closer the linear interpolated result approximates the spline interpolated original. 3.3 Web Interface The outcome of the overall methodology is an approach to online visualization and immersion that lets any standard web browser display interactive 3D dressed bodies without the need for extra plugins or downloads. For the purposes of wide public Internet access, the first VRML97 output directly from the garment simulator (MIRACloth - 3DSMax plugin) is used. Therefore, it is possible to view it locally or across the network without any special dedicated viewer. This allows a large-scale diffusion of the content over the W.W.W without increasing the cost of distribution. The models performed satisfactory in Internet Explorer with a rendering performance of 20 to 35 frames per second. A snapshot is shown in Figure 11. Figure 11 – The Virtual Try On: The online cloth catalogue (left) and the 3D viewer/extended java class (right) The models exported from the 3D Garment Simulator described before were integrated in the Virtual Try On suite to offer a Virtual Fitting Room service. The major considerations that determined the quality of the Virtual Fitting Room application were: • • • • The high quality rendering realism: (The geometry of the object was correctly perceived to include all its desired features). Additionally, antialiasing techniques, smooth shading and texture mapping were the most important factors that improved the rendering quality. The high quality of the animation, depending largely on the number of frames that can be redrawn on the display during a unit of time. (We keep in mind that while correct motion perception starts at 5 frames per second, good animation contains at least 15 frames per second). The interactive possibilities, these are related to how the user can move around the scene and visualize the objects through modification of viewing parameters (spins, body sizes, change transforms etc.) The response time that should be minimal. (The user is not willing to spend more than a few minutes in the Virtual Fitting Room). The whole process of dressing the customer and displaying the animations was fast enough. 4. Conclusions With respect to Macy’s fashion show, the high-end interactivity that they introduced was unparalleled till now. They have included virtual humans and several cloth catalogues, so that the viewer’s sense of participation and interaction is increased. We have introduced a new methodology to create step by step a Virtual Try On, starting from the creation of standard bodies, animating them, dressing them and then creating an interface to make them available on a Virtual Try On on the Internet. Based on realistic properties the behavior of our cloth simulation is highly realistic and this is visibly evident when viewing our VTO and comparing our results with previous work. We have succeeded to introduce a complete chain of processes for making bodies and clothes optimized for Internet usage in a Virtual Fitting Room. The bodies created with our approach correspond to real human body shapes as the human body measurements were derived from anthropometric sizing surveys and were modeled appropriately to be entirely animatable. The approach to design the clothes was merged with the fashion house approach to address the requirements of a cloth designer. Furthermore we simulated the physical parameters of the garments aiming to give to the user the feeling of the cloth behavior in order to be as close as possible to reality. 5. Future work The next goal, for several researchers in MIRALab, is to dynamically change the body measurements of a virtual human in order to move from the existing dressed bodies according to sizes to dressed bodies according to individual measurements. We have already decided to use the standard open specifications and we have opted for the H-Anim format that is part of the MPEG4 and X3D specification. The main issue is the implementation of realistic deformations, as H-Anim bodies are segmented, as well as animation file format. We are currently working on an inhouse solution in the form of an API that allows for virtual human real-time deformation, animation and integration with the 3D environment. 6. Acknowledgements This work is supported by the IST European project ‘E-TAILOR’. We like to thank Pascal Volino and Frederic Cordier for the development of the MIRACloth software, Tom Molet for the development of the motion tracking software, and our partners in E-TAILOR for the business analysis of the market. We like to thank Sabine Schechinger for her contribution in the making of the male, body and cloth, collection. Special thanks are due to Chris Joslin, Pritweesh De and George Papagiannakis for proof reading this document. References [1] Forrester Research, Apparel's On-line Makeover, Report, May 1999, http://www.forrester.com/ER/Research/Report/0,1338,5993,00.html [2] Brian Beck, Key Strategic Issues in Online Apparel Retailing, yourfit.com, 2000, Version 1.0 [3] Welcome to My Virtual Model(TM), http://www.landsend.com/ [4] NORDSTROM, http://www.nordstrom.com [5] Macy's Passport 99 Fashion Show http://www.shoutinteractive.com/Fashion/index.html [6] Volino P., Magnenat-Thalmann N., Implementing Fast Cloth Simulation with Collision Response, Computer Graphics International 2000, June 2000. [7] Weil J., "The Synthesis of Cloth Objects", Computer Graphics (SIGGRAPH’86 proceedings), Addison-Wesley, 24, pp 243-252, 1986. [8] Yang Y., Magnenat-Thalmann N., "Techniques for Cloth Animation", New trends in Animation and Visualisation, John Wiley & Sons Ltd, pp 243-256, 1991. [9] Carignan M., Yang Y., Magnenat- Thalmann N., Thalmann D.,"Dressing Animated Synthetic Actors with Complex Deformable Clothes", Computer Graphics (SIGGRAPH’92 proceedings), Addison-Wesley, 26(2), pp 99-104, 1992. [10] Volino P., Courchesne M., Magnenat-Thalmann N., "Versatile and Efficient Techniques for Simulating Cloth and Other Deformable Objects", Computer Graphics (SIGGRAPH’95 proceedings), Addison-Wesley, pp 137-144, 1995. [11] Breen D.E., House D.H., Wozny M.J., "Predicting the Drap of Woven Cloth Using Interacting Particles", Computer Graphics (SIGGRAPH’94 proceedings), Addison-Wesley, pp 365-372, July 1994. [12] Eberhardt B., Weber A., Strasser W., "A Fast, Flexible, Particle-System Model for Cloth Draping", Computer Graphics in Textiles and Apparel (IEEE Computer Graphics and Applications), pp 52-59, Sept. 1996. [13] Eischen J.W., Deng S., Clapp T.G., "Finite-Element Modeling and Control of Flexible Fabric Parts", Computer Graphics in Textiles and Apparel (IEEE Computer Graphics and Applications), pp 71-80, Sept. 1996. [14] HOHENSTEIN (DE), Workpackage 7 Input, Project No: IST-1999-10549, Internal Project Consortium document, July 2001 [15] Molet, T., Aubel, A., Çapin, T. et al (1999), ANYONE FOR TENNIS?, Presence, Vol. 8, No. 2, MIT press, April 1999, pp.140-156. [16] Oxford Metrics (2000) Real-Time Vicon8 Rt. Retrieved 10-04-01 from: http://www.metrics.co.uk/animation/realtime/realtimeframe.htm [17] MotionAnalysis, (2000) Real-Time HiRES 3D Motion Capture System. Retrieved 17-04-01 from: http://www.motionanalysis.com/applications/movement/research/real3d.html [18] Bodenheimer B., Rose, C., Rosenthal, S., & Pella, J. (1997). The Process of Motion Capture: Dealing with the Data. Eurographics workshop on Computer Animation and Simulation’97, Springer-Verlag Wien, 3-18. [19] Volino P., Magnenat-Thalmann N., Comparing Efficiency of Integration Methods for Cloth Simulation, Proceedings of CGI'01, Hong-Kong, July 2001. [20] Volino P., Magnenat-Thalmann N., Virtual Clothing Theory and Practice, ISBN 3-540-67600-7, Springer-Verlag, Berlin Heidelberg, New York [21] VRML97, The VRML97 The Virtual Reality Modeling Language International Standard ISO/IEC 14772-1:1997, http://www.vrml.org/Specifications/VRML97/ [22] Polevoi R., Interactive Web Graphics with Shout3D, ISBN 0-7821-2860-2, Copyright 2001 SYBEX Inc. Alameda [23] Babski C., Thalmann D., A seamless Shape For HANIM Compliant Bodies [24] Seo H., Cordier F., Philippon L., Magnenat-Thalmann N., Interactive Modelling of MPEG-4 Deformable Human Body Models, Postproceedings Deform 2000, Kluwer Academic Publishers. pp. 120~131. [25] LECTRA SYSTEMS – MODARIS V4 http://www.lectra.com/dyna/produits/modarisv4gb3ac477f005907.pdf
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