11 resultados para Multimedia Approach

em Deakin Research Online - Australia


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The 10MMM multimedia project began in late 2002 in a rural region of  western Victoria and has now entered its second stage. It is an interagency initiative intended to decrease the social isolation of rural young people and stimulate the expression of youth 'voice' and leadership using multimedia tools. As the process of working with rural young people unfolds over time, it provides an opportunity for ongoing reflection on the extent to which the project can become truly driven by young people, and whether it can enable them to take a stronger leadership role in their rural communities.

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Multimedia content understanding research requires rigorous approach to deal with the complexity of the data. At the crux of this problem is the method to deal with multilevel data whose structure exists at multiple scales and across data sources. A common example is modeling tags jointly with images to improve retrieval, classification and tag recommendation. Associated contextual observation, such as metadata, is rich that can be exploited for content analysis. A major challenge is the need for a principal approach to systematically incorporate associated media with the primary data source of interest. Taking a factor modeling approach, we propose a framework that can discover low-dimensional structures for a primary data source together with other associated information. We cast this task as a subspace learning problem under the framework of Bayesian nonparametrics and thus the subspace dimensionality and the number of clusters are automatically learnt from data instead of setting these parameters a priori. Using Beta processes as the building block, we construct random measures in a hierarchical structure to generate multiple data sources and capture their shared statistical at the same time. The model parameters are inferred efficiently using a novel combination of Gibbs and slice sampling. We demonstrate the applicability of the proposed model in three applications: image retrieval, automatic tag recommendation and image classification. Experiments using two real-world datasets show that our approach outperforms various state-of-the-art related methods.

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Students’ learning experience can be affected by difficulties in understanding the interrelationships between concepts and also between topics. Concept maps have been used in many disciplines (Kremer & Gains, 1996) to structure information and express relationships between them. Their holistic approach with multiple pathways through the learning resource can make relationships and linkages between topics and subtopics obvious, and contribute to a meaningful and positive learning experience. This paper outlines the development and formative evaluation of two hypermedia concept maps which led to the development of a series of eleven concept maps to enhance the learning experience of students in a first year undergraduate business law unit.

As part of the Stage 1 formative evaluation, two concept maps were developed together with supporting multimedia resources and trialled on the learners. Feedback was also obtained from technical staff. This phase was designed to assess and control the quality of the learning resource as well as the impact it had on the learning experience. The paper closes by discussing how information gained in Stage 1 was used in Stage 2 as a basis to modify the initially trialled maps and to develop the other supporting maps.

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This thesis presents a research work based on an integrated multi-modal approach for sports video indexing and retrieval. By combining specific features extractable from multiple (audio-visual) modalities, generic structure and specific events can be detected and classified. During browsing and retrieval, users will benefit from the integration of high-level semantic and some descriptive mid-level features such as whistle and close-up view of player(s). The main objective is to contribute to the three major components of sports video indexing systems. The first component is a set of powerful techniques to extract audio-visual features and semantic contents automatically. The main purposes are to reduce manual annotations and to summarize the lengthy contents into a compact, meaningful and more enjoyable presentation. The second component is an expressive and flexible indexing technique that supports gradual index construction. Indexing scheme is essential to determine the methods by which users can access a video database. The third and last component is a query language that can generate dynamic video summaries for smart browsing and support user-oriented retrievals.

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In this paper, we discuss a special case of knowledge creation via pattern mining that was studied using a hermeneutic approach. The reported study explores the nature of knowledge creation by domain practitioners who do not communicate directly. The focus of this paper extends the traditional view of a knowledge creation process beyond organisational boundaries. The proposed knowledge creation framework explains the facilitated process of knowledge creation by its qualification, combination, socialisation, externalisation, internalisation and introspection, thus allowing the transformation of individual experience and knowledge into formalised shareable domain knowledge.

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Multimedia information is now routinely available in the forms of text, pictures, animation and sound. Although text objects are relatively easy to deal with (in terms of information search and retrieval), other information bearing objects (such as sound, images, animation) are more difficult to index. Our research is aimed at developing better ways of representing multimedia objects by using a conceptual representation based on Schank's conceptual dependencies. Moreover, the representation allows for users' individual interpretations to be embedded in the system. This will alleviate the problems associated with traditional semantic networks by allowing for coexistence of multiple views of the same information. The viability of the approach is tested, and the preliminary results reported.

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Streaming applications over Mobile Ad-hoc Networks (MANET) require a smooth transmission rate. The Internet is unable to provide this service during traffic congestion in the network. Designing congestion control for these applications is challenging, because the standard TCP congestion control mechanism is not able to handle the special properties of a shared wireless multi hop channel well. In particular, the frequent changes to the network topology and the shared nature of the wireless channel pose major challenges. In this paper, we propose a novel approach, which allows a quick increase of throughput by using explicit feedback from routers.

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Multimedia content adaptation allows the ever increasing variety of handheld devices such as Smartphones to access distributed rich media resources available on the Internet today. Path planning and determination is a fundamental problem in enhancing performance of distributed multimedia content adaptation systems. Most of the existing path determination mechanisms use static path determination criteria based solely on associating a path with a single behavior aggregate score. However, some criteria such as availability are best represented using different functionality rather than being accumulated into the aggregate score. Moreover, since selection criteria have different behavior towards the score, this principle need to be considered. In this paper, we propose a dynamic multi-criteria path determination policy that selects an optimal path to the content adaptation services that best meet the user preferences and QoS requirements. The performance of the proposed approach is studied in terms of score’s fairness and reliability under different variations. The results indicate that the proposed policy performs substantially better than the baseline policy.

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Electronic information is becoming increasingly rich in content and varied in format and style while at the same time client devices are getting increasingly varied in their capabilities. This mismatch between rich contents and the end devices capability presents a challenge in providing seamless and ubiquitous access to electronic documents to interested users. Service-oriented content adaptation has emerged as a potential solution to the content-device mismatch problem. Since an adaptation task can potentially be performed by multiple content adaptation services (CAS), an approach for CAS discovery is a fundamental component of service-oriented content adaptation environment. In this paper, we propose a service discovery approach that considers the client device capability and the service’s attributes to discover appropriate CAS while optimizing performance and functionality. The efficiency of the proposed CAS discovery protocol is studied experimentally. The results show that the proposed discovery approach is effective in terms of discovering appropriate content adaptation services.