To improve safety at mass events, an evacuation assistant that supports security services in case of emergencies is developed. One central aspect is forecasting the emergency egress of large crowds in complex buildings. This requires realistic models of pedestrian dynamics that can be simulated faster than real-time by using methods applied in high performance computing. We give an overview of the project and present the actual results. We also describe the modeling approaches used thereby focusing on the runtime optimization and parallelization concepts. Copyright © 2012 John Wiley & Sons, Ltd.

To improve safety at mass events, an evacuation assistant that supports security services in case of emergencies is developed. One central aspect is forecasting the emergency egress of large crowds in complex buildings. This requires realistic models of pedestrian dynamics that can be simulated faster than real-time by using methods applied in highperformance computing. The results in terms of level of services and congestion areas are presented to the decision makers via a web interface.

Conversations between two people are ubiquitous in many inhabited contexts. The kinds of conversations that occur depend on several factors, including the time, the location of the participating agents, the spatial relationship between the agents, and the type of conversation in which they are engaged. The statistical distribution of dyadic conversations among a population of agents will therefore depend on these factors. In addition, the conversation types, flow, and duration will depend on agent attributes such as interpersonal relationships, emotional state, personal priorities, and socio-cultural proxemics. We present a framework for distributing conversations among virtual embodied agents in a real-time simulation. To avoid generating actual language dialogues, we express variations in the conversational flow by using behavior trees implementing a set of conversation archetypes. The flow of these behavior trees depends in part on the agents' attributes and progresses based on parametrically estimated transitional probabilities. With the participating agents' state, a ‘smart event’ model steers the interchange to different possible outcomes as it executes. Example behavior trees are developed for two conversation archetypes: buyer–seller negotiations and simple asking–answering; the model can be readily extended to others. Because the conversation archetype is known to participating agents, they can animate their gestures appropriate to their conversational state. The resulting animated conversations demonstrate reasonable variety and variability within the environmental context. Copyright © 2012 John Wiley & Sons, Ltd.

Conversations are ubiquitous in inhabited spaces. The statistical distribution of dyadic conversations depends on several factors, including the time, the location of the participating agents, their spatial relationship, and the type of conversation in which they are engaged. The conversation types, flow, and duration will depend on agent attributes such as interpersonal relationships, emotional state, personal priorities, and socio-cultural proxemics. We present a framework for distributing and animating conversations among virtual embodied agents in a real-time simulation.

Virtual characters in games and simulations often need to plan visually convincing paths through a crowded environment. This paper describes how crowd density information can be used to guide a large number of characters through a crowded environment. Crowd density information helps characters avoid congested routes that could lead to traffic jams. It also encourages characters to use a wide variety of routes to reach their destination. Our technique measures the desirability of a route by combining distance information with crowd density information. We start by building a navigation mesh for the walkable regions in a polygonal two-dimensional (2-D) or multilayered three-dimensional (3-D) environment. The skeleton of this navigation mesh is the medial axis. Each walkable region in the navigation mesh maintains an up-to-date density value. This density value is equal to the area occupied by all the characters inside a given region divided by the total area of this region. These density values are mapped onto the medial axis to form a weighted graph. An A^* search on this graph yields a backbone path for each character, and forces are used to guide the characters through the weighted environment. The characters periodically replan their routes as the density values are updated. Our experiments show that we can compute congestion-avoiding paths for tens of thousands of characters in real-time.Copyright © 2012 John Wiley & Sons, Ltd.

This paper describes how crowd density information can be used to guide a large number of characters through a crowded environment. Crowd density information helps characters avoid congested routes which could lead to traffic jams. The characters periodically replan their routes as the density values are updated. Our experiments show that we can compute congestion-avoiding paths for tens of thousands of characters in real-time.

Content-based human motion retrieval is important for animators with the development of motion editing and synthesis, which need to search similar motions in large databases. Obtaining text-based representation from quantization of mocap data turned out to be efficient. It becomes a fundamental step of many researches in human motion analysis. Geometric features are one of these techniques, which involve much prior knowledge and reduce data redundancy of numerical data. We describe geometric features as basic unit to define human motions (also called mo-words) and view a human motion as a generative process. Therefore, we obtain topic motions, which possess more semantic information using latent Dirichlet allocation by learning from massive training examples in order to understand motions better. We combine probabilistic model with human motion retrieval and come up with a new representation of human motions and a new retrieval framework. Our experiments demonstrate its advantages, both for understanding motions and retrieval. Copyright © 2011 John Wiley & Sons, Ltd.

In this work, we show an unsupervised method to extract a latent semantic layer based on geometric features, which provides a new way to represent and understand human motion capture data. This new semantic layer is composed by the combination patterns of mo-words which frequently apper in motions.

The visual world around us displays a rich set of light effects because of translucent and participating media. It is hard and time consuming to render these effects with scattering, caustic, and shaft because of the complex interaction between light and different media. This paper presents a new rendering method based on adaptive lattice for lighting participating media of translucent materials such as marble, wax, and shaft light. Firstly, on the basis of the lattice-based photon tracing model, multi-scale hierarchical lattice was constructed by mixed lattice types sampling combined cubic Cartesian and face-centered cubic with view-dependent adaptive resolution. Then, an adaptive method to trace diffuse photons and marked specular photons with different phase functions was suggested. Multiple lights and heterogeneous materials were also considered here. Further, the mixed rendering method and GPU accelerate technology were introduced to render different light effects under different participating media. Copyright © 2011 John Wiley & Sons, Ltd.

A novel lattice-based model with multi-scale hierarchical lattice based on photon tracing is proposed for lighting participating media of translucent materials such as marble, wax and shaft.Multiple lights and heterogeneous materials were also considered. The mixed rendering and GPU technology were introduced for quick rendering under different participating media.

The seamless integration of virtual characters into dynamic scenes captured by video is a challenging problem. In order to achieve consistent composite results, both the virtual and real characters must share the same geometrical constraints and their interactions must follow some common sense. One essential question is how to detect the motion of real objects—such as real characters moving in the video—and how to steer virtual characters accordingly to avoid unrealistic collisions. We propose an online solution. First, by analysis of the input video, the motion states of the real pedestrians are recovered into a common world 3D coordinate system. Meanwhile, a simplified accuracy measurement is defined to represent the confidence of the motion estimate. Then, under the constraints imposed by the real dynamic objects, the motion of virtual characters are accommodated by a uniform steering model. The final step is to merge virtual objects back to the real video scene by taking into account visibility and occlusion constraints between real foreground objects and virtual ones. Several examples demonstrate the efficiency of the proposed algorithm. Copyright © 2011 John Wiley & Sons, Ltd.

We proposed a video-based mixed reality system enabling interaction between real and virtual humans in real scenes. The virtual characters are modeled to move around the scene, keeping away from real obstacles and other virtual characters. At last, we integrate the virtual characters into the video seamlessly.

We present a technique to parameterize skin deformation by skeletal motion and to transfer the deformation style from one character to another. We decompose skin deformation into time-varying signals and basis matrices by using dimension reduction techniques and then approximate the time-varying signals by using radial basis functions with respect to joint angles that define skeletal motion. This decomposition reduces the size of deformation data to a small number of time-varying signals that represent the complex role of muscle action. The subsequent parameterization yields a fast and intuitive control of characters; thus, it allows us to construct faithful skin deformations quickly as skeletal bones move. The representation of our parameterization allows us to capture and transfer a derived deformation style to another skeleton–skin structure without considering the input dimension of the deformation data. This style transfer can be used as a basis for realistically animating variants of sample characters that have the same skeletal topology. Parameterization of skin deformation and its style transfer can be performed within a small amount of error once the preprocessing time and control of the deformation is carried out in real time by our graphics processing unit implementation. Copyright © 2011 John Wiley & Sons, Ltd.

We present a method to parameterize skin deformation by skeletal motion in order to represent the deformation with a small amount of data and to provide a fast and intuitive control. We also present a method to transfer the deformation style from one character to another using simple matrix computations within a small amount of error.

This paper presents a subdivision connectivity remeshing approach for closed genus 0 meshes. It is based on spherical parameterization and umbrella-operator smoothing. Our main contribution lies in adopting a low-distortion spherical parameterization approach to generate high-quality subdivision connectivity meshes. Besides, a simple and efficient point location method on the sphere based on the uniform partition of the rectangle is presented, which is used to find the containing triangle in the spherical mesh for each point on the sphere rapidly. Our method can generate high-quality subdivision connectivity meshes fast, which can be applied to level of detail and progressive transmission. All the application examples demonstrate that our remeshing procedure is robust and efficient. Copyright © 2011 John Wiley & Sons, Ltd.

We presented a subdivision connectivity remeshing approach for closed genus 0 meshes. Our main contribution lies in adopting a low-distortion spherical parameterization approach to generate high-quality subdivision connectivity meshes. Besides, a simple and efficient point location method on the sphere based on the uniform partition of the rectangle is presented. Our method can generate high quality subdivision connectivity meshes fast, which can be applied to level of detail and progressive transmission very well.

An augmented reality book (AR book) is an application in which such multimedia elements as virtual 3D objects, movie clips, or sound clips are augmented to a conventional book using augmented reality technology. It can provide better understanding about the contents and visual impressions for users. For AR books, this paper presents a markerless tracking method, which recognizes and tracks a large number of pages in real-time, even on PCs with low computation power. For fast recognition with respect to a large number of pages, we propose a generic randomized forest that is an extension of a randomized forest. In addition, we define the spatial locality of the subregions in an image to resolve the problem of a dropping recognition rate under a complex background. For tracking with minimal jittering, we also propose the adaptive keyframe-based tracking method, which automatically updates the current frame as a keyframe when it describes the page better than the existing one. Copyright © 2011 John Wiley & Sons, Ltd.

This paper presents a markerless tracking method for augmented reality book, which recognizes and tracks a large number of pages in real-time. For recognition, we propose a generic randomized forest that is an extension of a randomized forest and the spatial locality of the subregions in an image to resolve recognition problem under a complex background. As a tracking method, we propose an adaptive keyframe-based tracking method, which automatically updates a keyframe when it describes the page better than the existing one.

Biomechanical modeling of soft tissue is a complex problem for achieving realistic surgical simulations, surgical planning, and scientific analysis. In the literature, three categories of biomechanical models: spline based models, spring models, and finite element models (FEMs) are mainly used for dealing with this problem. Among these, spline based models offer relatively fast and realistic soft tissue simulations by utilizing both the spring and FEMs. In this paper, a new dynamic volume spline model for human face skin is proposed and the performance of our model is discussed by estimating the results of facial surgery of three different patients. Face models of the patients are obtained from 3D CT/MR scans by segmenting the skull, muscle, and skin layers. In these face models, the skull and the muscle layers are considered as the rigid boundary for the skin layer and the skin layer is modeled by our dynamic volume spline. The control points of the dynamic volume spline are localized masses with viscoelastic material properties (stiffness, damping, and mass). These parameters are computed from the skin material properties that were published in the literature. Once the face models are generated, facial surgery plannings are simulated. Infact, the pre-surgery face models are modified according to the surgical plans and the estimated post-surgery face models are compared with the actual post-surgery face models. Moreover, in order to discuss the performance of our dynamic volume spline model, the same analyses are performed on the post-surgery estimations of a conventional tool. Copyright © 2011 John Wiley & Sons, Ltd.

A dynamic volume spline model for human face skin is proposed and the performance of the model is discussed by estimating the results of facial surgery of three different patients. Face volume models of the patients are obtained from 3D CT/MR scans by segmenting the skull, muscle, and skin layers. In these face models, the skull and the muscle layers are considered as the rigid boundary for the skin layer and the skin layer is modeled by the dynamic volume spline.