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Integrated Projects

Demo for the “Simulating the Body and Motion of an Athlete” Integrated Project


All R&D activities within the 3DLife Network of Excellence are organized under a series of Integrated Projects (IPs). Each one of these IPs involves a different set of 3DLife partners, rotating in its leadership every six months. The list of 3DLife IPs is given in the table below.

The 3DLife Integrated Projects
Title Duration Involved Partners Poster Demo
Autonomous Virtual Humans M1 – Today QMUL, ITI, UNIGE AVH Poster (33) -
Audio Visual Analysis M1 – Today QMUL, DCU, ITI, TPT - -
Robust Virtual Mirror M1 – Today DCU, HHI, ITI RVM Poster (38) Link
Simulating the Body and Motion of an Athlete M1 – Today QMUL, DCU, UNIGE, TPT ABMS Poster (33) Link
Immersive Worlds M7 – Today ITI, UNIGE, TPT IW Poster (32) Link


Autonomous Virtual Humans. In this integrated project, UNIGE is developing an Embodied Conversation Agent system by integrating its own technologies for 3D graphics, animation techniques and dialogue management. The dialogue management will accept text and speech based input and will react in speech with the appropriate facial expressions. QMUL is working on recording head and the gaze movements of individual humans using a tracking device in a predefined dialogue. Based on this data, QMUL and UNIGE develop a model for facial gesture and eye-gaze controlled by specific dialogue events. The head and gaze model is being integrated into the Embodied Conversation Agent system. ITI develops a Face Recognition module that is also being integrated with the Embodied Conversation Agent system. Face recognition starts by detecting the face region in each frame of the video. This is based on low-level features of the image and is carried out in real-time. The output of this process is a bounding box of the face where face recognition takes place. Another set of low level features is being computed in the face bounding box, which serves as the basis for face matching. Matching in turn is based on specialized classifiers which try to classify the input unknown face to the most similar person of those registered in the database. The system is able to register new users when commanded by the dialogue manager. Registration might be done in bulk, that is many users together, or in separate, that is adding a new user to an already existing database. After each registration, the system undergoes a training process, not visible to the user, which is necessary for running algorithms. After training, the system is able to recognize anyone of the registered users by retrieving his/her name and presenting it to the dialogue manager. [Top]


Audio Visual Analysis. This integrated project aims to develop enabling technologies that could make interaction between humans in virtual on-line environments easier, more reliable and more realistic. Technologies that could make this vision accessible to all, irrespective of geographical location or access device. In order to reach this goal, integration of recent progress in 3D data acquisition and processing, autonomous avatars, real-time rendering, interaction in virtual worlds and networking is required. As such, this integrated project will foster collaboration between all consortium members involved in Activity 4.2 of the project. This strategic vision will be building upon the shorter term integrated projects that have been developed by consortium members starting from Month 7 of the 3DLife network of excellence. In addition, it will stimulate further integration of technologies between 3DLife members. The focus of this integrated project in the first instance will be on the development of a “ballet master class” scenario. In this vision, an experienced ballet dancer will deliver a performance to a predefined audio track. This performance will be captured in detail by accurate optical motion capture rig and rendered as a realistic avatar in an on-line virtual ballet studio. Students, on viewing the ballet teachers performance, will attempt to replicate the movements in synchrony with the same audio track, which will remain invariant to each data capture session. The real-time animation of each student’s avatar in the virtual environment will be driven by whatever 3D capture technology is available to him/her. This may be multiple camera rigs, inertial measurement units, optical motion capture rigs, or other suitable technologies. Analysis of each student’s performance will be made, highlighting areas requiring improvement. This integrated project aims to develop enabling technologies that could make interaction between humans in virtual online environments easier, more reliable and more realistic. Technologies that could make this vision accessible to all, irrespective of geographical location or access device. In order to reach this goal, integration of recent progress in 3D data acquisition and processing, autonomous avatars, real-time rendering, interaction in virtual worlds and networking is required. As such, this integrated project will foster collaboration between all consortium members involved in Activity 4.2. This strategic vision will building upon the shorter term integrated projects that have been developed by consortium members starting from Month 7 of the 3DLife network of excellence. In addition, it will stimulate further integration of technologies between 3DLife members. The focus of this integrated project in the first instance will be on the development of a “ballet master class” scenario. In this vision, an experienced ballet dancer will deliver a performance to a predefined audio track. This performance will be captured in detail by accurate optical motion capture rig and rendered as a realistic avatar in an online virtual ballet studio. Students, on viewing the ballet teachers performance, will attempt to replicate the movements in synchrony with the same audio track, which will remain invariant to each data capture session. The real-time animation of each student’s avatar in the virtual environment will be driven by whatever 3D capture technology is available to him/her. This may be multiple camera rigs, inertial measurement units, optical motion capture rigs, or other suitable technologies. Analysis of each student’s performance will be made, highlighting areas requiring improvement. [Top]


Robust Virtual Mirror. In this integrated project, we focus on the environment of a virtual dressing room.

Clothing is usually purchased by trying it on in front of a mirror. We look at how the fabric drapes our body and how we like the blend of colours and textures; and we do so while asking our friends to give us their opinion directly in the dressing room. However, when buying customized and tailored clothes, we purchase something that has not been produced yet. An augmented reality dressing room, equipped with a Virtual Mirror that shows the client wearing a virtual version of the customized product could assist the user in the selection of design, fabrics, textures and patterns, and thereby bring back the shopping experience when buying customized and tailored clothes.

During the development of such a system several issues have to be addressed. On the one hand, methods and algorithms for realistic rendering of virtually textured clothes or virtual clothes onto the real person have to be investigated, such that the virtual clothes accurately follow the movements of the body. On the other hand, in order to allow a large amount of cloth textures, also image retrieval is of great importance. In order to make the shopping experience a shared experience with friends, also the issue of streaming over networks to remote devices and data privacy could be addressed. [Top]


Simulating the Body and Motion of an Athlete. The objective of this integrated project is to simulate a realistic virtual human body model in motion.

In this integrated project, several advanced tools and computer graphics methods are used to achieve the visual realism.

As a real case scenario, simulation of a tennis player in motion will be demonstrated.

The production pipeline of this integrated project consists of the following stages:
- Firstly a human model is scanned and post-processed to generate high quality mesh with texture.
- Secondly these models are processed for scalable rendering.
- Thirdly the resulting high quality mesh is mapped to an animation library.
- Fourthly, corresponding motion data is generated.
- Finally the resulting model is streamed through network and rendered in an interactive environment for a visual demonstration. [Top]


Immersive Worlds. Immersive environments are the new big thing in infotainment since interactive and social media TV are just around the corner and IP and 3D TV are already here.

Giving the power to the end-user to dynamically construct his/her own immersive worlds based on his preferences and selected session parameters is the motivation behind the “Immersive Worlds” integrated project.

In order to achieve this goal, new tools should be developed that will provide an intuitive user experience and push the end-user to discover new ways of interaction with the media content available in the Future Internet.

The “Immersive Worlds” IP started at M7 of the 3DLife project lifetime; that is July 2010. Its initial timeline extends to M20 of the 3DLife project lifetime, i.e. August 2011.

During this initial timeline a tool was developed that enables the average user to easily create and view its own personalized virtual 3D worlds by using any available multimedia content (e.g. his own sketches, existing images, 3D models he found by searching the internet etc.).

Beyond August 2011 – from M21 up to M42 of the 3DLife project – the ultimate aim of the IP is to offer the possibility of a personalized immersive 3D experience to the user. This will be achieved by enhancing the aforementioned tool so as to enable the user to add a personal avatar as well as autonomous agent feeds, in the virtual 3D world. [Top]

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