[[alternative]]A Web-Based Cross-Cultural Collaborative Learning Environmnet for Science Education

計畫編號：NSC90-2520-S032-009研究期間：200108~200208研究經費：870,000[[sponsorship]]行政院國家科學委員

On the design of Web-based interactive multimedia contents for English learning

[[abstract]]We present a Web-based authoring tool to create interactive multimedia contents for English learning. Target users of this authoring tool are English teachers and content designer, therefore, ease of use and simplicity are the fundamental issues. Furthermore, the authoring tool and multimedia database are integrated in the context of intelligent Web-based interactive language learning (IWiLL) system. Special language tools to access corpus, manipulate multimedia elements, and create collaborative learning sessions are designed in the system. These resources and tools on hand yield the potential to create rich and deep interactive multimedia contents[[conferencetype]]國際[[conferencedate]]20040831~20040831[[booktype]]紙本[[conferencelocation]]Joensuu, Finlan

On the construction of a color model for real-time visual moving objects segmentation

[[abstract]]A color model, called RGB-Ellipse, is developed in this paper. The proposed color model takes advantages of CIE-L*a*b*94 and CMC(l:c) in determining color differences. Furthermore, the transformation between RGB and RGB-Ellipse is linear. As a result, we are able to manipulate the noise tolerance processing as well as the computation efficiency in dealing with color differences. By using the above features, we develop a real-time moving objects segmentation scheme. The developed segmentation scheme consists of two main steps: (1) region seed determination and region growing and (2) region-based change detection and background update. The results from a visual surveillance system are given to highlight the value of the proposed color model and moving objects segmentation scheme.[[notice]]補正完畢[[incitationindex]]E

[[alternative]]Intelligent Networked Visual Monitoring and Control Systems (II)

計畫編號：NSC89-2218-E032-019研究期間：200008~200107研究經費：647,000[[sponsorship]]行政院國家科學委員

The Designing of an Image Management System for Lecturing and Learning

[[abstract]]We present an image management system, called CanFind, for lecturing and learning. The designed web-based image management system aims to facilitate lecture and learning activity design purposes. It supports the following special features such as user personalization, semantic image retrieval, and systematic browsing. In order to provide semantic image retrieval feature, we integrate keyword extraction and keyword expansion schemes in the construction of indexing for the corresponding images. As a result, the demand images can be retrieved under the abstract level of images. Meanwhile, images upload and sharing functions are embedded in the system. As a result users may share their personal works among users. We have implemented the above system for the online and classroom lecture and the learning activity designs at Tamkang University.[[conferencetype]]國際[[conferencedate]]20020909~20020912[[conferencelocation]]Kazan, Tatarstan, Russi

[[alternative]]The Designing of Images Database by Using Bootstrapping

計畫編號：NSC94-2520-S032-005研究期間：200508~200607研究經費：768,000[[abstract]]在網際網路發達的現今社會，圖像素材庫已經非常的普遍。但是專門為了教學而設計的圖片分類系統，卻是少之又少。而本計畫『教學導向圖片分類系統之設計』將以教學為出發點，設計圖像檢索系統，促進學習者的學習效果。 本計畫所提出之系統具有以下特色： 1. 以自助式建構法建立圖片分類 我們建立圖片分類的依據為自助式建構法，首先手工建立少量的學門關鍵字，利用這些關鍵字當成查詢，然後在網路上收集相關網頁。再從網頁裡面做關鍵字擷取，擷取出新的關鍵字將成為下一次查詢的關鍵字集合。利用這樣方式反覆運作，可得一個比較客觀的方式來建立圖片的分類。 2. 利用字義分析來增加圖片檢索之精確度 我們利用關鍵字延伸來將圖片檢索時的回收率提高，但是漫無目的的延伸則會得使圖片檢索時的精確度下降。我們利用了字義分析來確定語意關鍵字的確實字義，縮小關鍵字延伸的範圍，增加了圖片檢索的精確度。 在圖像檢索研究領域裡，我們已經累積了相當的成果。因此，在本計畫中，為了要建置一套完整的教學導向圖片分類系統，我們將會把這一些成果和上述的特色整合起來，期待能在教學領域裡有更大的貢獻。[[sponsorship]]行政院國家科學委員

A real-time segmentation scheme for continuous color images

[[abstract]]A real-time segmentation scheme for continuous color images is presented in this paper. The proposed scheme consists of two main steps: (1) seed searching and region growing, (2) region-based change detection. A new color representation model, RBG-Ellipse, is proposed. This color model is similar to the HSI representation. However, the transformation between RGB and RGB-Ellipse is linear. Therefore, we are able to take advantage of noise tolerance processing as well as the efficiency in dealing with color difference computation. By using the proposed segmentation scheme, we implemented applications, (1) intelligent networked visual monitoring system and (2) user interface for distance learning to highlight the value of the proposed scheme. Users can view the results through our web site, http://www.can.tku.edu.tw.[[conferencetype]]國際[[conferencedate]]20010506~20010509[[booktype]]紙本[[conferencelocation]]Sydney, NSW, Australi

On the Approach of Automatic Adjustments for Gaussian-Mixture Clustering

[[abstract]]In this paper, we discuss the dual-problem of adjusting the mixture number and avoiding local optima in the estimation of a Gaussian mixture. This estimation is widely used in unsupervised-classification applications; however, its results are serially sensitive to the initial setting, which is difficult to optimize. It is also difficult to automatically designate the mixture number in advance. In much of the literature, these two issues are discussed separately, meaning that one is considered at the expense of the other. To overcome this problem, we present some strategies that automatically and simultaneously adjust the mixture number and escape from local optima. The evaluation results are very encouraging and show that the proposed strategies are effective.[[notice]]補正完畢[[incitationindex]]E

[[alternative]]Design and Implementation of Image Database for Lecturing (III)

計畫編號：NSC93-2520-S032-001研究期間：200408~200507研究經費：842,000[[sponsorship]]行政院國家科學委員

Design of networked visual monitoring systems

[[abstract]]We design and implement a networked visual monitoring system for surveillance. Instead of the usual periodical monitoring, the proposed system has an auto-tracking feature which captures the important characteristics of intruders. We integrate two schemes, namely, image segmentation and histogram comparison, to accomplish auto-tracking. The developed image segmentation scheme is able to separate moving objects from the background in real time. Next, the corresponding object centroid and boundary are computed. This information is used to guide the motion of tracking camera to track the intruders and then to take a series of shots, by following a predetermined pattern. We have also developed a multiple objects tracking scheme, based on object color histogram comparison, to overcome object occlusion and disocclusion issues. The designed system can track multiple intruders or follow any particular intruder automatically. To achieve efficient transmission and storage, the captured video is compressed in the H.263 format. Query based on time as well as events are provided. Users can access the system from web browsers to view the monitoring site or manipulate the tracking camera on the Internet. These features are of importance and value to surveillance.[[notice]]補正完畢[[incitationindex]]E