5598037
Supporting Information Reuse for Video Data Indexing by Using Color Information
In this paper, an object tracking framework assisted by image segmentation and color indexing techniques to support information reuse for video data is proposed. In order to obtain more accurate results of object tracking, a color indexing method called Color Label Criteria (CLC) is adopted to relax some of the restrictions and assumptions in object tracking in our previous work with low additional cost. Our experiment results on a real video sequence show that the CLC color indexing method is very helpful to achieve more robust object tracking.
11885669
A decision tree-based multimodal data mining framework for soccer goal detection
We propose a new multimedia data mining framework for the extraction of soccer goal events in soccer videos by using combined multimodal analysis and decision tree logic. The extracted events can be used to index the soccer videos. We first adopt an advanced video shot detection method to produce shot boundaries and some important visual features. Then, the visual/audio features are extracted for each shot at different granularities. This rich multimodal feature set is filtered by a pre-filtering step to clean the noise as well as to reduce the irrelevant data. A decision tree model is built upon the cleaned data set and is used to classify the goal shots. Finally, the experimental results demonstrate the effectiveness of our framework for soccer goal extraction.
9847925
A multimedia semantic model for RTSP-based multimedia presentation systems
An abstract multimedia semantic model called the multimedia augmented transition network (MATN) model is proposed to model the RTSP-based (real-time streaming protocol) multimedia presentation systems. RTSP provides a set of methods to support the functionality of "VCR-like" remote control on the client side so that users are allowed to control playback of the streaming media. The MATN model is used to model RTSP actions as well as temporal relations and synchronization control of the media streams. The advantages of using the MATN model are its simplicity, effectiveness, and ease of modification. Furthermore, a formal definition of the MATN model and modeling of RTSP actions using the MATN model are presented in detail.
16767212
A Robust Method for Biological Sequence Clustering
In this paper, we proposed a two-phase hybrid method for biological sequence clustering, which combines the strengths of the hierarchical agglomerative clustering methods and the partition clustering methods. In phase I, the hybrid method uses the hierarchical agglomerative clustering algorithm to pre-cluster the aligned sequences, while in the second phase it takes the pre-clustering result as the initial partition for the profile hidden Markov models (HMMs) based k-means partition clustering method. Such initial partitions (generated from phase I), as against random initial partitions, are usually more reasonable and thus can avoid the inconsistency problem in the partition clustering methods due to the randomness in initial partitions. In addition, the inaccuracy of the hierarchical agglomerative clustering methods can be compensated by the profile HMM based k-means partition clustering since the latter is model-based and can better describe the dynamic properties of the data in a cluster. Experiments on a molecular sequence dataset demonstrate the effectiveness and the efficiency of the proposed hybrid clustering algorithm
5113927
An unsupervised segmentation framework for texture image queries
In this paper a novel unsupervised segmentation framework for texture image queries is presented. The proposed framework consists of an unsupervised segmentation method for texture images, and a multi-filter query strategy. By applying the unsupervised segmentation method on each texture image, a set of texture feature parameters for that texture image can be extracted automatically. Based upon these parameters, an effective multi-filter query strategy which allows the users to issue texture-based image queries is developed The test results of the proposed framework on 318 texture images obtained from the MIT VisTex and Brodatz database are presented to show its effectiveness.
1252952
Information reuse and system integration in the development of a hurricane simulation system
This paper presents our effort in designing and implementing an advanced hurricane simulation system on the platform of the World Wide Web for the purpose of supporting decisional processes and hazard mitigation. The development of the system is based on amalgamated methodologies which come from diverse disciplines and is an integration of a variety of techniques. Superior to other similar systems in hurricane study, our system assembles and utilizes information and techniques in a more flexible and robust manner by taking advantage of system layering technique, component modeling strategy and database technologies. Preliminary experiments have been conducted to demonstrate the performance of the system.
7423428
Optimal Power Allocation in Wireless Networks with Transmitter-Receiver Power Tradeoffs
For many wireless communication links, such as those employing turbo codes or sequentially-decoded convolutional codes, the power consumption of the decoder at the receiver depends on the received signal power and, hence, on the transmitted signal power. By transmitting a signal at a power higher than the minimum required for successful reception, the transmitter can “assist” the receiver by reducing the receiver decoding effort and thereby reducing the overall power consumption on the link. In this paper, we consider sender-receiver power tradeoffs in data-gathering trees. We formulate an optimization problem to optimally assign power to the nodes in the tree for maximizing the lifetime of the data-gathering tree, which is equivalent to the time until network partition due to battery outage. We propose a Binary Search Algorithm for optimal power assignment among nodes that maximizes the tree lifetime. Our Binary Search Algorithm can be easily extended to handle practical considerations such as node mobility and peak power constraints at nodes. Using turbo codes as an example of a channel coding technique, we demonstrate significant improvements in network lifetimes as a result of sender-receiver power tradeoffs. These improvements are observed under a wide variety of network conditions and are more pronounced in densely deployed networks and networks with asymmetric power costs.
34951978
A Top-Down Fingerprint Image Enhancement Method Based on Fourier Analysis
We present a top-down fingerprint image enhancement method which is based on Fourier analysis Our method takes advantage of two filtering methods in Fourier domain proposed previously and employs a top-down iteration filtering technique, which enables the enhancement procedure not to rely severely on an accurate estimation of ridge frequency and orientation and also enables us to make use of more than the local information in local fingerprint filtering Consequently, our method is robust to handle low quality fingerprint images Results of enhancement are presented for some representative fingerprint images.
6431749
Reasoning with Multimedia Information Using Symbolic Projection
In many multimedia application systems, it is not the final goal to retrieve the relevant multimedia information from different multimedia information sources. Rather, post-processing of the retrieved multimedia information is needed. For example, the retrieved information is used as "known facts". The systems will do some reasoning to obtain further conclusions based on these multimedia form "known facts". We call this reasoning with multimedia information. Most current research work in multimedia information processing is focused on multimedia information retrieval, but post-processing the retrieved information is more or less ignored. This paper explores the way to tackle this problem by using symbolic projection. A case study of reasoning with still image information is presented. Some extensions to symbolic projection-introducing auxiliary pictorial objects in symbolic pictures that need to be processed-are discussed. We expect this paper will stimulate further research on this important but ignored topic.
15177304
A new method of color image segmentation based on intensity and hue clustering
A new method of color image segmentation is proposed. It is based on the K-means algorithm in HSI color space and has the advantage over those based on the RGB space. Both the hue and the intensity components are fully utilized. In the process of hue clustering, the special cyclic property of the hue component is taken into consideration. The paper gives the definition of the distance and the center in the hue space, based on which the hue-clustering algorithm is implemented. Utilised in medical image processing, the new method gives a good performance.
206618709
Building an Ontology for Financial Investment
Intelligent agent technologies hold great promise for the financial services and investment industries such as portfolio management. In financial investment, a multi-agent system approach is natural because of the multiplicity of information sources and the different expertise that must be brought to bear to produce a good recommendation (such as a stock buy or sell decision). The agents in a multi-agent system need to coordinate, cooperate or communicate with each other to solve a complex problem. However, ontologies are a key component in how different agents in a multi-agent system can communicate effectively, and how the knowledge of agents can develop. This paper presents a case study in building an ontology in financial investment. The lessons we learned from the construction process are discussed. Based on our ontology development experience and the current development of ontologies, a framework of next generation ontology construction tools, which is aimed to facilitate the ontology construction, is proposed.