Transactions on Computational Science XII

Puppetry is a popular art form involving the process of animating the inanimate performing puppets. Puppet playing not only is controlled by artist’s hand motions but also follows physical laws and engineering principles. To implement a puppet playing scenario in virtual environments, an interactive animation system is designed by taking into account both the user’s hand motion and the constraints of puppet and environment. Here the hand motion is realtime captured and recognized through a new input device, namely SmartGlove. The animation system adapts IMHAP testbed for procedural animation and generates puppet animation based on both the procedural animation technique and motion capture data from SmartGlove. Thus the physical hand motion can either activate the designed procedural animation through motion recognition or tune the parameters of the existing procedural animation to generate new puppet motions. This system allows a user to directly control puppet animation while preserving the high accuracy of motion control. The animation results show that the association of hand motion can smoothly plan and generate each procedure animation and seamlessly blend the gap between key frames. The potential application and improvement of the current animation system are discussed.

Various Partial Differential Equations (PDEs) have been used in computer graphics for approximating surfaces of geometric shapes by finding solutions to PDEs, subject to suitable boundary conditions. The PDE boundary conditions are defined as 3D curves on surfaces of the shapes. We propose how to automatically derive these curves from the surface of the original polygon mesh. Analytic solutions to the PDEs used throughout this work are fully determined by finding a set of coefficients associated with parametric functions according to the particular set of boundary conditions. When large polygon meshes are used, the PDE coefficients require an order of magnitude smaller space compared to the original polygon data and can be interactively rendered with different levels of detail. It allows for an efficient exchange of the PDE shapes in 3D Cyberworlds and their web visualization. In this paper we analyze and formulate the requirements for extracting suitable boundary conditions, describe the algorithm for the automatic deriving of the boundary curves, and present its implementation as a part of the function-based extension of VRML and X3D.

In this work we propose a talking head system based on animating facial expressions using a template face generated from a Partial Differential Equation (PDE). It uses a set of pre-configured curves (as boundary conditions for the chosen PDE) to calculate an internal template surface face. This surface is then used to associate various facial features with a given 3D face object. Motion retargeting is then used to transfer the deformations in these areas from the template to the target object. The procedure is continued until all the expressions in the database are calculated and transferred to the target 3D human face object. Additionally the system interacts with the user using an artificial intelligence (AI) chatterbot to generate response from a given text. Speech and facial animation are synchronized using the Microsoft Speech API, whereby the response from the AI bot is converted to speech.

Current active 3D range sensors, such as time-of-flight cameras, enable acquiring of range maps at video frame rate. Unfortunately, the resolution of the range maps is quite limited and the captured data are typically contaminated by noise. We therefore present a simple pipeline to enhance the quality as well as improve the spatial and depth resolution of range data in real time. To improve the spatial resolution of range data, we first upsample the depth information with the data from high resolution video camera. And then, a new strategy is utilized to increase the sub-pixel accuracy. We show that these techniques can greatly improve the reconstruction quality, boost the resolution of the range data to that of video sensor while achieving high computational efficiency for a real-time application.

Haptic device enable the user to manipulate the molecules and feel interactions during the docking process in virtual environment on the computer. Implementation of force-torque feedback allows the user to have more realistic experience during force simulation and find the optimum docking positions faster. In this paper, we propose a haptic rendering algorithm for biomolecular docking with force-torque feedback. It enables the user to experience six degree-of-freedom (DOF) haptic manipulation in molecular docking process. The linear smoothing method was proposed to improve stability of the haptic rendering during molecular docking. Collaborative docking with two devices was implemented.

The current world economic situation makes it necessary to develop new ways of establishing commercial relationships. One possible solution is to explore the advantages of virtual worlds, and for this reason online virtual trade fairs are becoming more popular in the business world. They enable companies to establish a trade relationship with their customers without the need to visit them in person. This is very attractive for exhibitors because it can save them money, which is a priority for many companies today. In this line, this article presents a multiuser virtual trade fair developed using 3D game engine technologys. Users represented by avatars can interact with each other while they are visiting the virtual fair, which has some interactive objects included in the stands to provide information about the exhibitors. This virtual world is accessible online, and visitors only require a plug-in on their computers to be able to enter the virtual world. The game technology makes it possible to obtain a high degree of realism: very real lighting, cast shadows, collision detection, etc. Moreover, the virtual world presented builds the 3D objects automatically. Participants in the trade fair can customize their virtual stand and the application will generate the code necessary for its inclusion in the rendered virtual world.

Domestic and industrial robots, intelligent software agents, and virtual world avatars are quickly becoming a part of our society. Just like it is necessary to be able to accurately authenticate identity of human beings, it is becoming essential to be able to determine identities of the non-biological entities. This paper presents current state of the art in virtual reality security, focusing specifically on emerging methodologies for avatar authentication. It also makes a strong link between avatar recognition and current biometric research. Finally, future directions and potential applications for this high impact research field are discussed.

This paper concerns the navigation of a physical robot in real natural environments which have been previously scanned in considerable (3D and colour image) detail so as to permit virtual exploration by cybernavigation prior to mission replication in the real world. An on-board high speed 3D laser scanner is used to localise the robot (determine its position and orientation) in its working environment by applying scan matching against the model data previously collected.

The quality of situation awareness directly affects the decision making process for human soldiers in Military Operations on Urban Terrain (MOUT). It is important to accurately model situation awareness to generate realistic tactical behaviors for the non-player characters (also known as bots) in MOUT simulations. This is a very challenging problem due to the time constraints and the heterogeneous cue types in MOUT. Although there are some theoretical models on situation awareness, they generally do not provide computational mechanisms suitable for MOUT simulations. In this paper, we propose a computational model of situation awareness for the bots in MOUT simulations. The model forms up situation awareness quickly with key cues. It is also designed to work with some novel features. They include case-based reasoning, qualitative spatial representation and expectations. The effectiveness of the computational model is assessed with Twilight City, a virtual environment that we have built for MOUT simulations.

Generating human-like behaviors for virtual agents has become increasingly important in many applications, such as crowd simulation, virtual training, digital entertainment, and safety planning. One of challenging issues in behavior modeling is how virtual agents make decisions given some time-critical and uncertain situations. In this paper, we present HumDPM, a decision process model for virtual agents, which incorporates two important factors of human decision making in time-critical situations: experience and emotion. In HumDPM, rather than relying on deliberate rational analysis, an agent makes its decisions by matching past experience cases to the current situation. We propose the detailed representation of experience case and investigate the mechanisms of situation assessment, experience matching and experience execution. To incorporate emotion into HumDPM, we introduce an emotion appraisal process in situation assessment for emotion elicitation. In HumDPM, the decision making process of an agent may be affected by its emotional states when: 1) deciding whether it is necessary to do a re-match of experience cases; 2) determining the situational context; and 3) selecting experience cases. We illustrate the effectiveness of HumDPM in crowd simulation. A case study of two typical crowd scenarios is conducted, which shows how a varied crowd composition leads to different individual behaviors, due to the retrieval of different experiences and the variation of agents’ emotional states.

Interactions between individuals are inherently dependent upon trust, no matter if they occur in the real world or in cybercommunities. Over the past years, proposals have been made to model trust relations computationally, either to assist users or for modeling purposes in multi-agent systems. These models rely implicitly on the social networks established by participating entities (be they autonomous agents or internet users). However, state-of-the-art trust frameworks often neglect the structure of those complex networks. In this paper, we present a new approach allowing agent-based trust frameworks to leverage information from both trusted and untrusted witnesses that would otherwise be neglected. An effective and robust voting scheme based on an agreement metric is presented and its benefit is shown through simulations.

Since emotions play an important role in the daily life of human beings, the need and importance of automatic emotion recognition has grown with increasing role of human computer interface applications. Emotion recognition could be done from the text, speech, facial expression or gesture. In this paper, we concentrate on recognition of “inner” emotions from electroencephalogram (EEG) signals. We propose real-time fractal dimension based algorithm of quantification of basic emotions using Arousal-Valence emotion model. Two emotion induction experiments with music stimuli and sound stimuli from International Affective Digitized Sounds (IADS) database were proposed and implemented. Finally, the real-time algorithm was proposed, implemented and tested to recognize six emotions such as fear, frustrated, sad, happy, pleasant and satisfied. Real-time applications were proposed and implemented in 3D virtual environments. The user emotions are recognized and visualized in real time on his/her avatar adding one more so-called “emotion dimension” to human computer interfaces. An EEG-enabled music therapy site was proposed and implemented. The music played to the patients helps them deal with problems such as pain and depression. An EEG-based web-enable music player which can display the music according to the user’s current emotion states was designed and implemented.