In redirected walking techniques, curvature gain and bending gain, which are referred to as curvature manipulation, are important redirection gains. The applied gains can differ when multiple paths are mapped, and sudden changes in gain may cause discomfort. This study proposes quadratic curvature manipulation (QCM) based on the habituation mechanism to effectively reduce discomfort. This method quadratically adjusts the path curvature, thereby reducing user's perception of curvature changes. Furthermore, we introduce the segmented curvature change (SCC) mode that combines QCM with linear curvature manipulation to facilitate more natural gain transitions, thereby reducing discomfort. Two experiments were conducted. Experiment 1 examined the relationship between QCM parameters and gains at which users felt discomfort. Experiment 2 further examined the effects of different curvature change modes on discomfort. The results indicate that using the SCC mode in curvature manipulations is more effective than other methods in reducing discomfort.

For individuals in situations where their hands are occupied, no-handed touch interaction represents a significant yet underexplored area. In this paper, we investigate touch performance on screens using body parts (the nose, tongue, chin, elbow, and toe) rather than the hand. Experiments were conducted with 37 participants to analyze their touch interaction, where they selected targets using various body parts under different conditions. We employed the Dual-Gaussian model and Ternary-Gaussian model to describe the touch endpoints of these body parts. Based on the statistical criterion derived from the models, we proposed a no-handed assistive technology, which achieved up to a 24.4% improvement in tapping speed and a 58.47% increase in tapping accuracy. Additionally, this paper provides HCI developers with design guidelines for optimizing no-handed touch interaction interfaces.

Virtual reality (VR), particularly through multi-user VR systems, enhances collaboration and immersion. However, multi-team VR systems (MTVR), which allow several teams to interact, either by cooperating or competing, are less studied. Drawing inspiration from concepts in game theory, specifically the positive-sum game (PSG) and zero-sum game (ZSG), this study investigated the impact of inter-team competition modes at the team level and haptic feedback at the individual level on team flow and individual flow for the first time. An experimental MTVR that supports inter-team competition in a two-person vs two-person pattern was implemented first. Then, a$2 \times 2$within-subject experiment was conducted to examine the effects of different inter-team competition modes (PSG/ZSG) and haptic feedback (on/off). The results based on 188 participants indicate that the PSG mode leads to significantly higher levels of collective ambition and improved team relationships compared to the ZSG mode. Furthermore, providing haptic feedback can significantly enhance awareness of shared and personal task goals, resulting in more cautious performance during teamwork.

Moving target selection in multimedia interactive systems faces unprecedented challenges as users increasingly interact across diverse, dynamic contexts-from live streaming in moving vehicles to VR gaming in varying environments. Existing approaches rely on probabilistic models that relate endpoint distribution to target properties (size, speed). However, these methods require substantial training data for each new context and lack transferability across scenarios, limiting their practical deployment in diverse multimedia environments where rich multimodal contextual information is readily available. This paper introduces MAGNeT (Multimodal Adaptive Gaussian Networks), which addresses these problems by combining classical statistical modeling with context-aware multimodal method. MAGNeT dynamically fuses pre-fitted Ternary-Gaussian models from various scenarios based on real-time contextual cues, enabling effective adaptation with minimal training data while preserving model interpretability. We take experiments on self-constructed 2D and 3D moving target selection datasets under in-vehicle vibration conditions. Extensive experiments demonstrate that MAGNeT achieves lower error rates with few-shot samples, by applying context-aware fusion of Gaussian experts from multi-factor conditions.

Panoramic roaming with HMDs provides an immersive VR experience and the realism of user’s navigation in panoramic virtual environments (VEs) can be further enhanced by real-walking locomotion technology. However, the mismatched viewpoint height & fluctuation with the user’s visual senses may lead to perceptual conflicts during real-walking interaction. We conducted a series of user studies to investigate how viewpoint height & fluctuation affect the walking perception of users by real-walking interaction to navigate panoramic VEs and constructed a virtual camera motion model of viewpoint fluctuation and eyetracking compensation for walking behavior in panoramic virtual roaming. It was found that mismatched viewpoint fluctuation triggered generalized discomfort in participants and that participants preferred virtual viewpoint heights below eye level when roaming in panoramic VEs by real-walking. Considering these findings, we proposed viewpoint adaptive adjustment method based on visual manipulation and conducted a preliminary evaluation, which showed that the proposed method can effectively mitigate the conflict between the visual system and other sensory systems. It made that panoramic VEs constructed at a certain fixed height are rendered universal for users with different eyelevel heights and viewpoint fluctuation is matched to the undulation of their center of gravity during real-walking interaction.

Abstract Current VR/AR system development studios lack a toolkit that can automatically generate hierarchical tile menu layouts and menu prototypes for VR/AR devices without the need for user programming. This paper proposes a solution in the form of a toolkit that automatically generates a hierarchy tile menu layout using a modified circular treemap algorithm. Users can interactively arrange and resize tiles to create various layouts according to their preferences or needs, utilizing a circle packer method. The toolkit further automatically generates a VR/AR menu prototype based on the resulting layout. Notably, reprogramming is not necessary each time the hierarchy is modified or the menu layout is redesigned. The user test results demonstrate that the proposed toolkit simplifies the creation of hierarchical tile menu layouts, enhances user efficiency in the design process, and enables users to flexibly create hierarchical tile menu prototypes according to their design ideas.

Summary Reaction time, the ability to detect, process and respond to stimuli, is one of the fundamental factors in human computer interaction, and is a key cognitive skill in clinical and healthy populations. Good reaction time allows us to respond to stimuli and situations with agility and efficiency. How to train and improve a person's reaction time has become an important research question. In this paper, we present a new training genre which combines the user‐centered personalized training objects generation with precise tracking of foot interaction.Virtual objects are created with respect to the user's features and historical training effectiveness, and are in motion. A foot tracking algorithm based on three‐Gaussian model is designed to support interaction with stepping on moving virtual objects. We present the design and implementation of the system, as well as user studies. Findings illustrate that the reaction time performances are significantly improved following of seven days of training based on foot interaction.

Online fitness training, with its affordability and flexibility, offers a convenient way for individuals to engage in regular workouts that promote physical and mental health. Yet, learning fitness motions in this way presents various challenges and may not always be as effective as in-person training. To address the practical demands of motion learning, we conducted a systematic survey and accordingly proposed a four-stage self-learning genre that integrates immersive virtual reality (VR) environments with motion skill learning theories, strategies, and expert experience. Herein, we merged progressive structures and multi-level visual cues to enhance instruction, and proposed a fine-grained motion analysis method to provide adaptive correction feedback during training. Utilizing a Taichi training platform with the genre embedded, we systematically validated the effectiveness of the genre, and examined the potential impact of VR content presentation form on motion learning among different age groups, as well as their preferences and focus on VR fitness training genre design. Results from the quantitative analysis, qualitative evaluation, and case study showed that the 360° video-based VR content brought more positive motion learning performance and user experiences than the fully-simulated VR used in many previous studies. The proposed genre demonstrated outstandingly performance, experience, and usability, with each stage and design playing an effective role. Moreover, we offer several design considerations for VR fitness systems targeting diverse age groups, providing beneficial insights for VR development in the sports and health-related fields.

The latest advancements in Virtual Reality (VR) enable the creation of 3D models within a holographic immersive simulation environment. In this article, we create QuickCSGModeling , a user-friendly mid-air interactive modeling system. We first prepare a dataset consisting of diverse components and precompute the discrete signed distance function (SDF) for each component. During the modeling phase, users can freely design complicated shapes with a pair of VR controllers. Based on the discrete SDF representation, any CSG-like operation (union, intersection, and subtraction) can be performed voxel-wisely. Also, we maintain a single dynamic SDF for the whole scene, whose zero-level set surface exactly encodes the most recent constructed shape. Both SDF fusion and surface extraction are implemented via GPU for a smooth user experience. A total of 34 volunteers were asked to create their favorite models using QuickCSGModeling. With a simple training, most of them can create a fascinating shape or even a descriptive scene quickly. We also discuss how to extend our system to create articulated models with hinges, where an adaptive cube subdivision has to be enforced to improve the reconstruction accuracy around the hinge part, followed by a Dual Contouring-based surface extraction. 1

Distributed ray tracing algorithms are widely used when rendering massive scenes, where data utilization and load balancing are the keys to improving performance. One essential observation is that rays are temporally coherent, which indicates that temporal information can be used to improve computational efficiency. In this paper, we use temporal coherence to optimize the performance of distributed ray tracing. First, we propose a temporal coherence-based scheduling algorithm to guide the task/data assignment and scheduling. Then, we propose a virtual portal structure to predict the radiance of rays based on the previous frame, and send the rays with low radiance to a precomputed simplified model for further tracing, which can dramatically reduce the traversal complexity and the overhead of network data transmission. The approach was validated on scenes of sizes up to 355 GB. Our algorithm can achieve a speedup of up to 81% compared to previous algorithms, with a very small mean squared error.

The curvature gain of redirected walking method enables users to explore virtual spaces that are larger than real spaces. The estimation of human sensitivity for curvature gain is important for redirected walking. Herein, we conduct two experiments under different path conditions. By adopting the psychophysical “method of limits” to be a new approach, the first experiment re-estimates the sensitivity for a curved path and further proves that people are more sensitive for right-curved paths than left-curved paths. The second experiment investigates the characteristics of preorder paths on the sensitivity to postorder paths, and finds that the existing of preorder paths significantly increases the sensitivity for the postorder path. Moreover, we find an interesting moderation effect on the direction consistency of preorder and postorder paths: the larger curved preorder path can significantly decrease the sensitivity for postorder path when they have the same direction. If their directions diverge, the effect of preorder path is not significant.

Modeling error rates in moving target selection is critical in guiding the design and improving user performance in the user interface with dynamic contents. Despite the high accuracy of existing models in predicting error rates for various inputs, they need to fit a large number of samples for a specific interaction scenario. This paper presents a scenario adaptive model that can quickly learn the characterizes of endpoints from small data in a specific scenario, and then accurately predict the error rates in this scenario. We report on two studies evaluating the adaptability of the model in specific users (children and the older user) and pointing postures (walking and one-handed) with a smartphone. Significant improvements in error rates prediction of our model were observed compared to the previous non-adaptive one. We conclude with the findings from our results for insights into future interface design.

Along with the development of network and virtual reality (VR), VR-based telerobotic systems have been widely applied in many fields, especially in hazardous or uncertain environments. But the existing navigation methods of remote robot are implemented by operators using keyboard, mouse joystick, or walking-in-place devices in the VR environments that is telepresence of remote environments. In this paper, we propose a new navigation method for VR-based telerobotic system via operators' real walking in a limited physical space, wherein the motion of a remote robot is synchronized with that of an operator who is actually walking in a limited physical space while naturally interacting (head and body interaction) with the robot and experiencing the remote environment with the help of VR video real-timely captured by the robot. This makes the operators have better sense of presence at the remote sites than the existing methods. We design and implement a system based on this technology, and the test shows that it can make the robot flexible to be navigated in remote complex and dynamic environments.

A mobile app interface usually consists of a set of user interface modules. How to properly design these user interface modules is vital to achieving user satisfaction for a mobile app. However, there are few methods to determine design variables for user interface modules except for relying on the judgment of designers. Usually, a laborious post-processing step is necessary to verify the key change of each design variable. Therefore, there is only a very limited amount of design solutions that can be tested. It is time-consuming and almost impossible to figure out the best design solutions as there are many modules. To this end, we introduce FEELER, a framework to fast and intelligently explore design solutions of user interface modules with a collective machine learning approach. FEELER can help designers quantitatively measure the preference score of different design solutions, aiming to facilitate the designers to conveniently and quickly adjust user interface module. We conducted extensive experimental evaluations on two real-life datasets to demonstrate its applicability in real-life cases of user interface module design in the Baidu App, which is one of the most popular mobile apps in China.

The flow experience-performance link is commonly found weak in virtual environments (VEs). The weak association model (WAM) suggests that distraction caused by disjointed features may be associated with the weak association. People characterized by field independent (FI) or field dependent (FD) cognitive style have different abilities in handling sustained attention, thus they may perform differently in the flow-performance link. To explore the role of the field dependence-independence (FDI) construct on the flow-performance link in virtual reality (VR), we developed a VR experimental environment, based on which two empirical studies were performed. Study 1 revealed FD individuals have higher dispersion degree of fixations and showed a weaker flow-performance link. Next, we provide visual cues that utilize distractors to achieve more task-oriented attention. Study 2 found it helps strengthen the task performance, as well as the flow-performance link of FD individuals without increasing distraction. This paper helps draw conclusions on the effects of human diversity on the flow-performance link in VEs and found ways to design a VR system according to individual characteristics.

A serious challenge that confronts shapelet-based algorithms for time series classification is finding optimal shapelets in a short time. Representative shapelet-discovery algorithms find shapelets by evaluating the qualities of candidates extracted from the subsequences. One of the main difficulties is the large amount of time consumed, due to the excessive number of shapelet candidates. To address the above problem, in this paper we propose a fast and interpretable candidate-extraction algorithm to accelerate the process of shapelet discovery. The proposed algorithm utilizes a time series subclass splitting technique to sample time series dataset first. Then, an IDP (Important Data Point)-based selective-extraction strategy is used to extract shapelet candidates. The generated candidates have significant improvements in quality and reductions in quantity. Furthermore, the shapelet candidates generated are more interpretable. To test the effectiveness of the shapelet candidates generated, we transform the original time series and use an off-the-shelf attribute-selection technique to select optimal shapelets from candidates. We then evaluate the proposed algorithm through extensive experiments. The results demonstrate that the proposed algorithm makes significant improvements in accuracy, compared with baselines. Meanwhile, the time consumption is also greatly reduced.

Weak association model indicates that distraction caused by the disjunction between the primary task and interactive artifacts may be a key factor directly leading to weak association between flow and task performance in virtual reality (VR) activities. To test the idea, this paper proposed a VR visual search paradigm based on which we constructed a VR oceanic treasure hunting system. Experiment 1 proved that distraction caused by the incongruence was indeed a direct antecedent of weak association. Next, we slightly adjusted the system by providing visual cues to achieve task-oriented selective attention. Experiment 2 found this helped enhance the task performance without damaging flow experience.

In this paper, we developed an agent-based virtual interview training system which can help college students with high shyness level to improve interview skills and reduce their anxiety by themselves before they take a real interview. The system includes three main contents: three virtual agents with different types of personality, three kinds of interview training contents and a multidimensional evaluation method, so that it is able to meet common demands of preparing for interviews. User study indicates the system can help shy college students cope with interview anxiety and improve their interview training performance effectively.

This paper presents a mixed reality storytelling system, which takes handicrafts as tangible interaction tools. Via the system, users can learn handicraft and then use the handicraft pieces to design, create and tell stories with HoloLens iteratively. In order to overcome the limitations of HoloLens gesture interaction, the system uses hand tracking with Kinect to implement a touch-like effect on the desktop. User study shows that our system has good usability, and it is welcomed by users. In addition, it can stimulate users interest in handicraft and storytelling, and even promote parent-child interaction effectively.

This paper presents a toolkit called Rotbav for easily constructing mixed reality (MR) apps that can be experienced in real time in large indoor physical space via HoloLens. It resolves the problem that existing MR devices, e.g. HoloLens, are unable to scan and model an entire large scene with several rooms at once. We introduce a custom data structure called VorPa, based on the Voronoi diagram, to implement path editing, accelerated rendering and location effectively. Our experiments and applications show that the toolkit is convenient and easy to use for constructing MR apps targeting large indoor physical spaces, in which users can roam in real time.

Background Due to the restriction of display mode, in most of the virtual reality systems with multiple people in the same physical space , the program renders the scene based on the position and perspective of the one user, so that other users just see the same scene, resulting in vision disorder. Methods To improve experience of multi-user co-located collaboration, in this study, we propose a fire drill system supporting co-located collaboration, in which three co-located users can collaborate to complete the virtual firefighting mission. Firstly, with multi-view stereoscopic projective display technology and ultra wideband (UWB) technology, co-located users can roam independently and watch virtual scenes through the correct perspective view based on their own position by wearing dedicated shutter glasses, thus carrying out different virtual tasks, which improves the flexibility of co-located collaboration. Secondly, we design simulated firefighting water-gun using the micro-electromechanical system sensor, through which users can interact with virtual environment, and thus provide a better interactive experience. Finally, we develop a workbench including a holographic display module and multi-touch operation module for virtual scene assembly and virtual environment control. Results The controller can use the workbench to adjust the virtual layout in real time, and control the virtual task process to increase the flexibility and playability of system. Conclusions Our work can be employed in a wide range of related virtual reality applications .

Many studies conducted in non-virtual activities have shown that flow significantly influences performance, yet studies in virtual activities often reveal only a weak association. This paper begins by building a theoretical explanatory model, and then conducts 3 empirical studies to explore this question. Study 1 exams the mechanism of weak association in two virtual activities. Study 2 tests the effectiveness of a potential approach to strengthen this association. In Study 3 we applied our proposed model and design approach to optimize a VR tennis game. Results show that the influence of flow on performance was not significant in those virtual activities where the primary task and the operation of interactive artifacts were less congruent such that the artifacts can lead to flow experience that is independently of the primary task. Our research offers a theoretical and empirical basis on how to optimize virtual environment design and maximize positive effect of the flow experience.

Stereoscopic display is a standard display mode for virtual reality environments. Typical 3D projection provides only a single stereoscopic video stream; thus co-located users cannot correctly perceive the virtual scene based on their own position and view. Several works devoted to developing multi-user stereoscopic display, but the number of users is very limited or the technical implementation is complicated. In this paper we put forward two flexible and simple projection-based multi-user stereoscopic display systems. The first one, named TPA, is based on a triple-projector array and provides a 120Hz active stereo for three users. Two TPAs can be combined to form a six-user system. The second one, named DPA, is a dual-projector and easy-implemented system providing individual stereoscopic video stream for two to six users. Finally, a co-located multi-user virtual fireman simulation training system and a virtual tennis simulation system were created to verify the effectiveness of our systems.

Big Data analytics service platform delivers a new type of public cloud offerings, through which end users can outsource their job executions by using a group of professional Big Data processing services in a pay-per-use way. Different from other type of cloud services, parallel jobs dominate the domain of data processing services, whose execution time can be varied greatly with different runtime configurations, such as different degrees of parallelism. In such a market-oriented environment, scheduling jobs from end users efficiently to optimize the Big Data analytics service platform's revenue is a more challenging task. In this paper, we propose a market-oriented heuristic algorithm for scheduling parallel jobs in a Big Data analytics service platform with admission control to optimize the platform operator's revenue. The proposed scheduling heuristic takes into account not only the dynamic revenue gained from accomplishing a job within a specific runtime as well as the consumption of resources needed for running it to achieve this given runtime, but also the potential loss it causes to the system by running this job instead of other waiting jobs currently in the system. We also propose a collaborative filtering based approach to quickly and accurately predict the execution time of parallel jobs running in a Big Data analytics service platform. We have conducted extensive experiments and simulations based on workload data derived from the real-world data analytics service platform and parallel applications. We show that our scheduler can outperform the other scheduling algorithms used for comparison, which are based on classical heuristics from literature, thereby fully evaluating the effectiveness of our market-oriented heuristic scheduling algorithm.

In this paper, we present a method of view-dependent stereoscopic projection on curved screen. It allows the user to walk around with the correct perspective view of the virtual scene consistent with his/her location. To solve the problem of distortion and drift of virtual objects when projecting the view-dependent scene images on curved screen, we operate a dynamic parallax adjustment of the stereoscopic images according to viewpoints. User evaluation shows that our proposed approaches are effective on improving visual experience.

With the fast development of virtual reality games, one of the key research questions is how players may express their creativity and participate in the process of game design. In this paper, we present a new game genre which combines user-controlled game design in physical space with game play in virtual space on a mobile device. The new system supports authoring by anyone, creating virtual reality games that can be easily modified or developed for physical space, and be used anywhere by novice end-users without any knowledge of tracking technology. We present the design and implementation of the system, as well as a user experiment. Findings illustrate that the proposed system promotes participation and provides a richer, more interactive and engaging experience.

In the case of a cloud-based remote control system such as SCADA (Supervisory Control and Data Acquisition) that enables users to collect data from cloud-connected machines deployed anywhere at any time. However, machine data models may not be updated in a timely manner after the devices are upgrades or modified. This leads to mismatches between the machine data and data models. A key obstacle of the matching is that the machines can be modified. To address this, we present a self-evolving method for machine data model. We give the description of the evolution of machine data models and the self-evolving method for the models in details. The method detects the conflicts between the machine data and models, and transfer or derive models if necessary. Our method can thus facilitate the evolution of machine data models and ensure that every machine in the cloud corresponds to the correct machine data model automatically. At last, we present two case studies to validate our method.

In virtual learning environment, both personality and emotional features of animated pedagogical agents (APAs) may influence learning. To investigate this question, we developed four APAs with two distinct personality types and two sets of gestures expressing distinct emotional feedback. Effects of APAs' personality types and emotional feedback strategies on learning experiences and performance were assessed experimentally using a virtual Tai Chi training system. Fifty six participants completed the experiment. Results showed that positive emotional feedback strategy led to better learning experiences and performance than negative feedback strategy. Moreover, personality type had significant effect on learning. Choleric APAs led to better performance than Phlegmatic APAs. Personality types moderated the effect of emotional feedback on learning satisfaction. Our study demonstrates that APAs with distinct personality types and emotional feedback are important design parameters for virtual learning environments.

With the development of intelligent manufacturing technology, it can be foreseen that time series data generated by smart devices will raise to an unprecedented level. For time series with high amount, high dimension and renewal speed characteristics, resulting in difficult data mining and presentation on the original time series data. This paper presented a piecewise linear representation based on importance data points for time series data, which called PLR_IDP for short. The method finds importance data points by calculating the fitting error of single point and piecewise, and then represents time series approximately by linear composed of the importance data points. Results from theoretical analysis and experiments show that PLR_IDP reduces the dimensionality, holds the main characteristic with small fitting error of segments and single points.

Poisson disk sampling is an important problem in computer graphics and has a wide variety of applications in imaging, geometry, rendering, etc. In this paper, we propose a novel Poisson disk sampling algorithm based on disk packing. The key idea uses the observation that a relatively dense disk packing layout naturally satisfies the Poisson disk distribution property that each point is no closer to the others than a specified minimum distance, i.e., the Poisson disk radius. We use this property to propose a relaxation algorithm that achieves a good balance between the random and uniform properties needed for Poisson disk distributions. Our algorithm is easily adapted to image stippling by extending identical disk packing to unequal disks. Experimental results demonstrate the efficacy of our approaches.

We propose a real-time rendering system for automatically creating a caricature drawing, i.e., an exaggerated portrait, of a human face, based on simultaneous use of a range image (or 3D mesh) and a registered photograph of the same face. Combining these information sources provides complementary information. Significant geometric lines such as occluding contours and suggestive contours are extracted from the range data, while textured areas corresponding to shading features are extracted from the photograph. These are combined, and then distorted to produce the final caricature. The final output may be produced using a choice of non-photorealistic rendering styles. Our system method works well for low resolution range images; for these it is fast enough to allow the viewpoint to be chosen in real time. The final output combines significant lines, textured areas, and optional shading, giving a pleasing result which preserves not only the shape cues of the geometric description, but also other essential visual characteristics of the facial image that cannot be deduced from geometry alone.

In geological engineering, stratum structure detection is a fundamental problem in project planning and implementation. One of the most commonly employed detection technologies is to take videos of borehole using a forward moving camera. Following this approach, the problem of stratum structure detection is transformed into the problem of constructing a panoramic image from the taken video sequences, which are typically in low quality. In this paper, we propose a novel method to create a panoramic image of the borehole from the video sequence without camera calibration and tracking. To stitch together pixels of neighboring frame images, our camera model is designed with a focal length changing feature, along with a small rotation freedom in the two-dimensional image space. Essentially, our camera model assumes target objects lie on a cylindrical wall and the camera moves forward along the central axis of the cylindrical wall. Our method robustly resolves these two degrees-of-freedoms through KLT feature tracking and constructs a panoramic image by stitching strips. Experiment results show that our method could efficiently generate high-quality panoramas for very long video sequences.

In this paper we design and implement a digital media service oriented digital museum platform based on Grid. We construct the whole system based on the Open Grid Service Architecture (OGSA), which supports flexibly constructing and deploying various digital media applications. The system shield the heterogeneity of resources via data access service so that the enormous dispersed resources can be effectively accessed and integrated. We also propose an on-demand application constructing method based on service composition. Using this method, we can implement digital media applications by dynamic service binding. Moreover, we implement digital media service applications based on this platform, such as 3D virtual museum walkthrough system.

Centroidal Voronoi tessellation (CVT) is a particular type of Voronoi tessellation that has many applications in computational sciences and engineering, including computer graphics. The prevailing method for computing CVT is Lloyd's method, which has linear convergence and is inefficient in practice. We develop new efficient methods for CVT computation and demonstrate the fast convergence of these methods. Specifically, we show that the CVT energy function has 2nd order smoothness for convex domains with smooth density, as well as in most situations encountered in optimization. Due to the 2nd order smoothness, it is possible to minimize the CVT energy functions using Newton-like optimization methods and expect fast convergence. We propose a quasi-Newton method to compute CVT and demonstrate its faster convergence than Lloyd's method with various numerical examples. It is also significantly faster and more robust than the Lloyd-Newton method, a previous attempt to accelerate CVT. We also demonstrate surface remeshing as a possible application.

Current smart mobile devices such as Pocket PCs have become common accepted daily-life personal assistants. Such mobile devices provide much less support for visualization compared to desktop computers. When developing mobile visualization applications, one should take the limited screen size, currently available interaction tools and relatively poor computation power into consideration. We describe a visual lens toolkit integrated with Focus+Context technique and it can be incorporated into various applications on Pocket PCs. Our technique creates a distorted display view of target object in a high resolution focus area that is smoothly embedded into the distorted context. We have tested the toolkit in two applications as stylistic lens and sketch lens separately and received fine experiment results. In remote line drawing of 3D model system, the lens toolkit embedded into the client side mainly serve as stylistic lens which provide the users with different presentation styles of the model according to the current viewpoint and focus. In mobile sketch system, the lens toolkit performs like a refinement filter which adoptively turns the loose sketch or SVG file into finer image. Both tested applications.

According to the CSCW cooperative mechanism, this paper presents the implementation of the distributed collaborative design platform based on pattern design, which is an application of CSCW in CAD. The architecture platform and protocol implementation is provided. It also describes the push and pulls functions used to perform data integrity and maintenance consistency. The applications show that the platform has features of CSCW to ensure that it operates well in real world conditions.

Digital museums become necessary when we have to present the precious collections to more and more visitors while preventing the state of preservation of the collections deteriorating over the time. It has significance to share and protect expensive museum resources. However, most current digital museum systems present the vast amount information in a static and primitive fashion and are not fully capable of dealing with generally heterogeneous and isolated resources. In this paper, we propose a grid-enabled digital museum system to improve the quality, availability and variety of the information presentation and sharing by incorporating grid-computing technologies. By designing cooperative grid services, we could efficiently and effectively organize, present and share the resources over the grid. The framework and workflow of the system are illustrated and the implementation details are also given.

This paper mainly discusses how to design a virtual museum system used by many users at the same time, and how to manage the scene data. To a 3D indoor scene, the empty scene (only the building) without other objects such as collections can be created by sweeping a 2D polygon along an axis which is perpendicular to the horizontal plane. We can create the scene polygon's Voronoi diagram, which subdivides the polygon into some cells called Voronoi regions by the proximity characteristic. An edge of the polygon corresponding to a wall of the building has its own Voronoi region where all the points are nearest to the edge than others. Hence, every user can select one Voronoi region to lay out collections such as cultural relics on the exhibition platform and every collection is saved by the Voronoi region in which it is laid out. Based on the scene polygon's Voronoi diagram, the system can also support multi-user cooperative interaction in the created scene very well. The work also can be used to create virtual art gallery, product exhibition hall and so on.

This paper describes a system framework of 3D virtual museum supporting multi-user cooperative interaction. To a 3D virtual museum, the building (empty scene) can be projected to a 2D polygon. Hence, we can manage the data of collections and users based on the scene polygon's Voronoi diagram. We can get the Voronoi diagram by subdividing the polygon into some cells using the proximity characteristic. We also establish some communication rules between users. In this article, how to compute visibility and detect collisions based on polygon's Voronoi diagram is discussed and this method is aimed to improve the reality and coherence of cooperative interaction in virtual museum.