29 research outputs found

    CyberWalk : a web-based distributed virtual walkthrough environment

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    A distributed virtual walkthrough environment allows users connected to the geometry server to walk through a specific place of interest, without having to travel physically. This place of interest may be a virtual museum, virtual library or virtual university. There are two basic approaches to distribute the virtual environment from the geometry server to the clients, complete replication and on-demand transmission. Although the on-demand transmission approach saves waiting time and optimizes network usage, many technical issues need to be addressed in order for the system to be interactive. CyberWalk is a web-based distributed virtual walkthrough system developed based on the on-demand transmission approach. It achieves the necessary performance with a multiresolution caching mechanism. First, it reduces the model transmission and rendering times by employing a progressive multiresolution modeling technique. Second, it reduces the Internet response time by providing a caching and prefetching mechanism. Third, it allows a client to continue to operate, at least partially, when the Internet is disconnected. The caching mechanism of CyberWalk tries to maintain at least a minimum resolution of the object models in order to provide at least a coarse view of the objects to the viewer. All these features allow CyberWalk to provide sufficient interactivity to the user for virtual walkthrough over the Internet environment. In this paper, we demonstrate the design and implementation of CyberWalk. We investigate the effectiveness of the multiresolution caching mechanism of CyberWalk in supporting virtual walkthrough applications in the Internet environment through numerous experiments, both on the simulation system and on the prototype system

    Recent development in multimedia e-learning technologies

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    Multimedia and networking technologies have significantly impacted on our daily activities, particularly in terms of how we learn. Nowadays, classroom teaching no longer simply relies on chalk and blackboard as the prime medium for course dissemination. E-learning technologies have made it possible to provide a virtual classroom environment on the Web through supporting teacher-student and student-student communications, course material distribution as well as online student assessments. They provide students with more control over their learning schedule and pace. On top of this, multimedia technologies further offer students different forms of media to match their learning styles, leading to enhancements of their learning effectiveness. This extended introduction discusses the latest e-learning specific multimedia technologies, their research challenges and future trends from both pedagogical and technological perspectives. We also summarize the papers included in this special issue

    Visual Tracking via Locality Sensitive Histograms

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    Contour-Based Warping

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    In this paper, a new warping technique called contour-based warping is presented. Feature contours of objects are defined and mapped to their target shapes. This allows the user greater flexibility in defining the warping with minimal effort. Two image warping methods are introduced in this paper and both are based on the concept of mapping contours. The peel-and-resample method can warp simple image objects with a single inner-feature in a short time, but suffers from the problems of misalignment and inability of handling multiple features. The wave propagation method solves these two problems. Unlike most existing methods, this method warps image objects based on specified feature contours instead of points or vectors. Results of this method demonstrate that increasing the number of contour features distributed on the warping image reduces the computational time. However, it is slower compared with the peel-and-resample method when warping simple image objects with a single inner-fea..

    Motion prediction for caching and prefetching in mouse-driven DVE navigation

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    A distributed virtual environment (DVE) allows geographically separated users to participate in a shared virtual environment via connected networks. However, when the users are connected by the Internet, bandwidth limitation and network latency may seriously affect the performance and the interactivity of the system. This explains why there are very few DVE applications for the Internet. To address these shortcomings, caching and prefetching techniques are usually employed. Unfortunately, the effectiveness of these techniques depends largely on the accuracy of the prediction method used. Although there are a few methods proposed for predicting 3D motion, most of them are primarily designed for predicting the motion of specific objects by assuming certain object motion behaviors. We notice that in desktop DVE applications, such as virtual walkthrough and network gaming, the 2D mouse is still the most popular device used for navigation input. Through studying the motion behavior of a mouse during 3D navigation, we have developed a hybrid motion model for predicting the mouse motion during such navigationā€”a linear model for prediction at low-velocity motion and an elliptic model for prediction at high-velocity motion. The predicted mouse motion velocity is then mapped to the 3D environment for predicting the userā€™s 3D motion. We describe how this prediction method can be integrated into the caching and prefetching mechanisms of our DVE prototype.We also demonstrate the effectiveness of the method and the resulting caching and prefetching mechanisms through extensive experiments

    VSculpt : a distributed virtual sculpting environment for collaborative design

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    A collaborative virtual sculpting system supports a team of geographically separated designers/engineers connected by networks to participate in designing three-dimensional (3-D) virtual engineering tools or sculptures. It encourages international collaboration at a minimal cost. However, in order for the system to be useful, two factors need to be addressed: intuitiveness and real-time interaction. Although a lot of effort has been put into developing virtual sculpting environments, only limited work addresses collaborative virtual sculpting. This is because in order to support real-time collaborative virtual sculpting, many challenging issues need to be addressed. In this paper, we propose a collaborative virtual sculpting framework, called VSculpt. Through adapting some techniques we developed earlier and integrating them with some techniques developed here, the proposed framework provides a real-time intuitive environment for collaborative design. In particular, it addresses issues on efficient rendering and transmission of deformable objects, intuitive object deformation using the CyberGlove and concurrent object deformation by multiple clients. We demonstrate and evaluate the performance of the proposed framework through a number of experiments

    L-0-Regularized image downscaling

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    Efficient Mirror Detection via Multi-Level Heterogeneous Learning

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    We present HetNet (Multi-level Heterogeneous Network), a highly efficient mirror detection network. Current mirror detection methods focus more on performance than efficiency, limiting the real-time applications (such as drones). Their lack of efficiency is aroused by the common design of adopting homogeneous modules at different levels, which ignores the difference between different levels of features. In contrast, HetNet detects potential mirror regions initially through low-level understandings (e.g., intensity contrasts) and then combines with high-level understandings (contextual discontinuity for instance) to finalize the predictions. To perform accurate yet efficient mirror detection, HetNet follows an effective architecture that obtains specific information at different stages to detect mirrors. We further propose a multi-orientation intensity-based contrasted module (MIC) and a reflection semantic logical module (RSL), equipped on HetNet, to predict potential mirror regions by low-level understandings and analyze semantic logic in scenarios by high-level understandings, respectively. Compared to the state-of-the-art method, HetNet runs 664% faster and draws an average performance gain of 8.9% on MAE, 3.1% on IoU, and 2.0% on F-measure on two mirror detection benchmarks. The code is available at https://github.com/Catherine-R-He/HetNet
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