Transactions on Edutainment XIII

With the development of information technology, digital museum has already been a quite beneficial method for the protection and communication of cultural heritage. For digital museums, interactive and multimedia technologies of exhibition greatly enrich visitor’s experience, and make it easier to gain insight into the connotation of different cultural exhibits vividly. With the consideration of balancing the tradeoff between the device cost and display effect, in this paper, we propose a digital museum exhibition system based on the combination of handheld projector and depth sensor. We treat the walls of common rooms as the projection screen, and then mapping virtual images, which reflect the real museum exhibitions, on these “walls”. Users can walk in the room freely, and browse images by changing the irradiation area of projector; furthermore, they can explore different virtual exhibition rooms by interacting with the projected virtual interface. Key procedures to realize the proposed virtual exploring system are described, and several experiments have been taken to test the usability and user experience of the proposed system, which is of low cost and easy to use, especially suitable for individual users and small organizations.

This paper proposes a CPI (conceptual-procedural-integrative) learning method for textiles and clothing university students to learn the computational design for clothing thermal functions and performance on knowledge, skills and application levels. First, the CPI learning method is discussed. Second, three proposed learning approaches (virtual trial learning, 3M learning, F/P-oriented design learning) on knowledge, skills and application in clothing thermal computational design are described. Third, the paper describes a course design and user study of a one-semester university apparel functional design course. The data of a pre-post study were collected. The results showed that the students achieved significant improvement in theoretical academic content on knowledge, skills and application.

Virtual Camera is an output window designed for three-dimensional graphics. This research on aesthetic computing of virtual camera is to improve artists’ working efficiency and to assist non-artists users’ aesthetic-related decision making in the use of the three-dimensional production software. In terms of photo composition, by setting the default value of controlled variables, automatically produced shot types can help the user to improve production efficiency greatly, as well as to simplify work flow. From the aesthetic point of view, aesthetic computing can provide users with more patterns for shot types selection.

Nowadays, high dimensional time series data draws more and more attention. But it is a great challenge to analyze high dimensional time series data. At present, typical methods for high dimensional time series data visualization, including ThemeRiver and Parallel Coordinates Plots, cannot reveal the distribution of the data state nor the evolution of data with time variation. And they also cannot explore the relationship between attributes of the high dimensional data and data state. In this paper, a synthetic visualization system combining Parallel Coordinates Plots and Multidimensional Scaling (MDS) is proposed for the analysis of multivariate time series data. The state distribution diagram is firstly achieved by mapping high dimensional series data onto the two-dimension space using MDS method. Distance of data points on the state distribution diagram reflects the similarity within time slices while the density indicates the state distribution of the dataset. The original dataset is then mapped on the Parallel Coordinates. Through the interaction of Parallel Coordinates and the state distribution diagram, users are able to detect evolution of time series data and explore the relationship within multiple dimensions under different states of data.

When visual and auditory are not available on some occasions, tactile rendering systems can provide an effective way for people to obtain information. A wearable tactile information expression system based on electrotactile rendering is designed and developed. Because this is a kind of passive stimulation, dynamic display method which displayed one electrode at a time according to some specific orders is necessary to improve the effect of perception of the proposed system and this method is applied on an 8 × 8 spherical electrode array to obtain information through people’s wrist. Three experiments including voltage threshold experiment, spatial resolution experiment and simple pattern recognition experiment are implemented and the average success rate of recognition is above 90%. These experimental results verify the effectiveness of the proposed system and lay a foundation for identifying complicated patterns in the future.

With the advanced development of the information technologies, more and more virtual environment applications and systems are based on network. Avatars are human being’s representatives in virtual world to demonstrate human being behaviors in the real world. It is necessary to have a coding standard for the avatar’s behaviors in order to interact more efficient and more understandable. In this paper, we propose an adaptable behavior coding schema for avatars’ interaction in the distributed virtual environment. The Huffman coding technique is adapted to minimize the average length of behavior codes based on a survey and its analysis. Meanwhile, a transmission coding schema is proposed. Demonstrations are built to approve our schema.

Gesture Recognition technology has been widely used in virtual reality and human-computer interaction. This paper proposed a virtual music control system based on dynamic hand gesture recognition. The system mode was mainly designed and realized by three modules including control terminal, client terminal and the server. By capturing the gesture image sequence via a cellphone camera, the system is able to recognize information characters of gestures such as number of fingers and movement of gesture trace. Control terminal generate different instructions and send them to client terminal via server. Relative experiments showed that the interaction system had good applicability and portability.

Hand gesture interaction has already become a research focus with the rapid development of virtual reality technologies. In this paper, we present a real-time interactive system based on hand gesture recognition in virtual fitting. Firstly, real-time data of hand gesture are captured by Leap Motion sensor. Then, we analyze the data and set the parameter projection to the hand model in virtual environment. Finally, the interaction with objects in the virtual environment will be realized by real-time gesture recognition. Application environment is designed as a virtual fitting room. Users can view virtual clothing by gesture interaction. Experiments show that the system is efficient and user friendly. And system’s gesture recognition has good real-time performance and accuracy.

A robust rectification algorithm for vision navigation system of the planetary rover is presented to rectify the stereo images based on the traditional projective rectification algorithm. In this algorithm, the projective matrix is calculated by corresponding points and then optimized using the parameters calibrated on the earth. This algorithm can resolve the parameter changing problem in soft-landing for planetary rover effectively. Experiments show that the results are almost same as the ones using calibrated rectification algorithm.

Interactive dynamic simulation method is proposed to solve computational models of soft tissue undergoing large deformation, collision detection, volume conservation in medical surgical simulation visualization. During the process of implementation of the interactive dynamic simulation method, the point based method is used to simulate the elastic solids undergoing large deformations and the position based method is used to simulate the objects collision, friction and volume conservation. It improves the efficiency and stability of the response of heterogeneous soft tissue undergoing contact or even the multi-organs interactions, and can be extended to interactive biopsy and cutting simulation.

The architectures of image acquisition and computation usually play important roles in most computer vision systems, especially in the multi-camera dynamic light-field acquisition and rendering systems for virtual reality. This paper designs a general distributed stream computing architecture to support light-field data stream acquisition and computation. Taking advantage of the distributed computing framework and in-memory high-speed processing engine, this architecture combines stream and batch processing together, which could reduce the computation burden. In order to evaluate the performance of proposed distributed stream computing architecture, we construct a dynamic light-field acquisition and rendering system, and the light-field data are obtained from a 10-meter-diameter and 7-meter-height hemispherical steel-frame dome that is equipped with 20 cameras and 2000 LED lightings. Experiments results show our system can continuously acquire and render light-field data at more than 1 frame per second with limited computational resources.

Visualization is the most intuitive expression to show scene inside or outside. Along with further study on three-dimensional terrain, rendering technology of terrain is not able to meet the high demands of picture clarity and fluency when render the scene. It is necessary to introduce numerical methods - material point method for accurate calculation of terrain deformation. Construct basic terrain by Geometry Clipmaps algorithm and then select NTVPM as dynamics model to interact with the terrain. The application of the material point method is for particle separation of terrain and calculation of force. Finally, the real-time rendering effect of rut is implemented by GPU. The experimental results show that the improved algorithm meets the truth and fluency of real-time terrain rendering. Observation from different viewpoints and comparative analysis before and after the application of the material point method on fps, CPU utilization.

This paper introduces new GPU-based color grading algorithms for real-time 3D scene rendering pipeline, to solve the problem of color bias, lack of lighting and brightness in common real-time rendering systems. A new real-time color grading solution is also provided to make use of the 3DLUT data along with parametric textures, to read and apply data on GPU side efficiently. These improve the rendering quality without distinct impacts to system efficiency and interactivity, and can be used widely in modern virtual reality and game developments.

The demand for 3D model retrieval is increasing, and the sketch-based method has been proven to be the most effective and efficient approach to retrieve 3D models. The existing methods calculate distance based on feature extraction, showing its limitation in improving retrieval accuracy. Thus, a second ranking making use of relevance between features is a good way to go. In this paper, an extended manifold ranking method is presented as a new retrieval framework. Line drawings are abstracted to represent 3D models, and a visual vocabulary is used to describe the local features of both sketches and line drawings. To rank the similarities between models, a method of semantic classification as a constraint is presented. We use similarity weight to control the classification difference between models so that the ranking score of models that belong to the same class holds a higher similarity weight. Furthermore, based on the idea of manifold learning, a KNN algorithm is adopted to obtain better ranking results. Experiments on standard testing datasets have demonstrated that the proposed algorithm significantly improves the accuracy of 3D model retrieval and outperforms current state-of-the-art algorithms by comparison.

Autonomous mobile robot is a completely unknown or partially unknown, of its complex environment, which requires the ability to avoid obstacles in order to move safely and avoid the collisions while navigating. To solve this problem, it opted to propose an obstacle avoidance algorithm and implement it as a Decentralized Software Services (DSS) service that uses and combines multiple of sonar and infrared (IR) sensors to detect obstacles including the corner form obstacles, glass obstacles … etc. The obstacle avoidance process is divided into two parts or states, the open state, in which the obstacles are detected, and the obstacles avoidance state in which obstacles are avoided. The obtained results demonstrate the success of the proposed algorithm in which the risk, of collisions, is excluded because the proposed solution controls, automatically, the robot speed and takes into consideration the robot width and the security distance while driving, detecting and avoiding obstacles.

The demand for 3D video content is growing. Conventional 3D video creation approaches need certain devices to take the 3D videos or lots of people to do the labor-intensive depth labeling work. To reduce the manpower and time consumption, many automatic approaches has been developed to convert legacy 2D videos into 3D. However, due to the strict quality requirements in video production industry, most of the automatic conversion methods are suffered from many quality issues and could not be used in the actual production. As a result manual or semi-automatic 3D video generation approaches are still mainstream 3D video generation technologies. In our project, we took advantage of an automatic video generation method and tried to apply human-computer interactions in its process procedure [1] in the aim to find a balance between time efficiency and depth map generation quality. The novelty of the paper relies on the successful attempt on improving an automatic 3D video generation method in the angle of video and film industry.

Collaborative work is a necessary model in urban management, it helps support multiple departments of the municipal government to speed the response of urban incident. Effective information transmission and exchange are important to implement the synchronous work among the information systems in multiple departments of municipal government. This paper proposes an approach of building a collaborative system based on multi-agent mechanism, to support urban management. A multi-agent collaborative model, which combines centralized and distributed management architecture, was developed. The collaborative work system has been applied and proved.

Traditional image features combined with different classifiers are widely used in existing vehicle logo recognition methods, which didn’t take into account the rich structure information of vehicle logos. Considering both their gray and structure information, a novel method based on foreground-background pixel pair (FBPP) feature, in which pixels are randomly sampled from foreground-background skeleton areas, is proposed. The pixel pair feature extraction process takes full consideration of vehicle logo structure, which makes this feature distinctive and discriminative. The experiment results show that, compared with methods based on features mainly focused on gray information, the method based on the proposed feature can achieve higher recognition performance. Especially under weak illumination, our method has shown strong robustness.

Content-aware image retargeting, also known as seam carving or content aware scaling, is an algorithm for image resizing developed in recent years. In this paper, we present a content-aware image retargeting method by combining the line-based Moving Least Squares (MLS) deformation and saliency map. We develop a salience-related weight of MLS deformation that allows manually defining regions in which pixels may not be moved. Therefore, the new image retargeting can change non-vital parts of the image while preserving local shapes in the areas with high saliency. Benefited from the line-based MLS deformation, our method can retarget image from rectangle to arbitrary polygon. When the constrained lines are at the interior of the boundary of image, our method can also deal with the artistic perspective manipulation problem well. The purpose of developing this algorithm is to display images without distortion on various media in the field of industrial, entertainment or artistic creation. Experimental results show that the proposed method outperforms existing methods in terms of visual performance.

Pesticide Residue is one of main sources resulted in food safety problems. It is necessary to analyze the distribution pattern of pesticide residue in order to supervision and management the overuse of pesticide. Thematic map is an effective approach for visualizing data combined with a specific geographic area. The most popular of the thematic maps are Choropleth, in which the values of the attribute are encoded as points or colored regions on the map. However, when the density of attribute-points on an area is different with that region’s area, the data overlap will be produced. In this paper, we present a method for visualizing multidimensional data based on Cartogram. With this method, we first create Cartogram and Choropleth for presenting the geospatial distribution of data at the same time in order to avoid data overlapping, in which the Cartogram is generated by using diffusion algorithm; Second, we create thematic geographic heat map for presenting the pesticide residue pollution index by means of Inverse Distance Weighted interpolation to reckon missing data, in which the pesticide residue pollution index is calculated by using multiple linear regression algorithm; Thirdly, a multi-view spatial-temporal data visualization system, which combines maps, time axis, bar chart, bubble chart, pie chart etc. is presented to help user analyzing the data. A variety of interactive means such as region selection, data filtering, time cursor dragging, are also introduced to the system. The system uses two different ways to combine spatial with time. The results of user evaluation demonstrated that our method and system can effectively help user to analyze geospatial distribution of pesticide residue pollution.

The shot is basic physical unit of video sequence, which is a collection of several consecutive frames in time and space that is captured by a camera. Shot boundary detection is the structural basis of video retrieval, the performance of detection algorithm will directly affect the efficiency of video retrieval. By describing and analyzing advantages and disadvantages of existing algorithms, this paper proposes a shot detection algorithm of self-adaptive dual thresholds based on multi-feature fusion. Firstly, frame difference is calculated by combining HSV color feature and LBP texture feature in the image that is non-uniformly divided into several blocks. Secondly, frame difference is compared with two self-adaptive thresholds to detect shot boundary. Finally, video is segmented some independent shots. Experiment analysis shows that this algorithm can’t only extract features that reflect main contents of video images, but also effectively detect abrupt shots and gradual shots. It reduces the number of false detection and miss detection, therefore, it has higher recall and precision than existing shot boundary detection algorithms. To a certain extent, this algorithm improves the efficiency of shot boundary detection.

Compared with the maturity of outdoor positioning technology, the indoor LBS (Location Based Services) are far less available. Yet, some applications such as virtual reality and augmented reality are in great need of services provided by indoor positioning technology. This paper presents an indoor positioning method and system based on iBeacons, which are a kind of low energy Bluetooth gadgets proposed by Apple. An array of iBeacons are deployed in an indoor environment to periodically emit signals which can be received by a mobile phone. The distance between the mobile phone and the iBeacons can be obtained by RSSI (Received Signal Strength Indication) ranging model. The position can be calculated according the three-ball positioning algorithm whenever three or more signals are received. A lot of experiments have been accomplished and the results show that the positioning accuracy can be acquired less than 1.1 m. Thus, the system can meet the requirements of many indoor positioning application scenarios.

Load balancing is an important technology to support parallel service in network. This paper presents a dynamic load balancing architecture with master/slave model. The architecture is used in a cluster monitoring system in order to use and distribute resources effectively. Dynamic library management mechanism is used to overly manage messages, and allocate tasks using path dispatch strategy. A network monitoring system of enterprise intranet based on web services has been developed which can provide short response time, high efficiency and efficient usage of resources.

When assessment information and preference information about alternatives are expressed through triangular fuzzy numbers, those numbers can be converted into identity-discrepancy-contrary connection numbers. Furthermore, multiple attribute decision-making is conducted using connection mathematics theory. The method is simple when attribute weights are unknown and it can both take full advantage of the valuator’s fuzzy information and satisfy the decision-maker’s preferences. Objective and reasonable fuzzy decision-making is accomplished under the precondition of avoiding the complex process of computing weights and identifying false decision-making caused by using the linear weighted sum model. The decision-making result using this method to solve a partner selection problem in virtual enterprises is similar to that of an established method based on expected values.

Feature weighting is an important task in data analyze, clustering and classification. Traditional algorithms focus on a common weight vector on the whole dataset which can easily lead to sensitiveness to the distribution of data. In contrast, a novel feature weighting algorithm called local feature weighting (LFW) that assign each sample a unique weight vector is proposed in this paper. We use clustering assumption to construct optimization task. Instead of considering the total intra-class and between-class features, we focus on the clustering performance on each training sample and the optimization goals are to minimize the total distances of a training sample to others in the same class and maximize the total distances in different classes. Data weight is added to the target function to emphasis nearby samples and finally use an iterative process to solve our problem. Experiments show that the new algorithm has a good performance on data classification. In addition, we provide a simple version of LFW which has less running time but with little accuracy loss.