A hybrid fractal video compression method

Fractal image compression is a relatively recent image compression method. Its extension to a sequence of motion images is important in video compression applications. There are two basic fractal compression methods, namely the cube-based and the frame-based methods, being commonly used in the industry. However there are advantages and disadvantages in both methods. This paper proposes a hybrid algorithm highlighting the advantages of the two methods in order to produce a good compression algorithm for video industry. Experimental results show the hybrid algorithm improves the compression ratio and the quality of decompressed images.

Matching search in fractal video compression and its parallel implementation in distributed computing environments

Fractal video compression is a relatively new video compression method. Its attraction is due to the high compression ratio and the simple decompression algorithm. But its computational complexity is high and as a result parallel algorithms on high performance machines become one way out. In this study we partition the matching search, which occupies the majority of the work in a fractal video compression process, into small tasks and implement them in two distributed computing environments, one using DCOM and the other using .NET Remoting technology, based on a local area network consists of loosely coupled PCs. Experimental results show that the parallel algorithm is able to achieve a high speedup in these distributed environments.

Adaptive partition and hybrid method in fractal video compression

Fractal image compression is a relatively recent image compression method, which is simple to use and often leads to a high compression ratio. These advantages make it suitable for the situation of a single encoding and many decoding, as required in video on demand, archive compression, etc. There are two fundamental fractal compression methods, namely, the cube-based and the frame-based methods, being commonly studied. However, there are advantages and disadvantages in both methods. This paper gives an extension of the fundamental compression methods based on the concept of adaptive partition. Experimental results show that the algorithms based on adaptive partition may obtain a much higher compression ratio compared to algorithms based on fixed partition while maintaining the quality of decompressed images.

Event models for tumor classification with SAGE gene expression data

Serial Analysis of Gene Expression (SAGE) is a relatively new method for monitoring gene expression levels and is expected to contribute significantly to the progress in cancer treatment by enabling a precise and early diagnosis. A promising application of SAGE gene expression data is classification of tumors. In this paper, we build three event models (the multivariate Bernoulli model, the multinomial model and the normalized multinomial model) for SAGE data classification. Both binary classification and multicategory classification are investigated. Experiments on two SAGE datasets show that the multivariate Bernoulli model performs well with small feature sizes, but the multinomial performs better at large feature sizes, while the normalized multinomial performs well with medium feature sizes. The multinomial achieves the highest overall accuracy.

Design of parallel algorithms for fractal video compression

The intrinsic independent features of the optimal codebook cubes searching process in fractal video compression systems are examined and exploited. The design of a suitable parallel algorithm reflecting the concept is presented. The Message Passing Interface (MPI) is chosen to be the communication tool for the implementation of the parallel algorithm on distributed memory parallel computers. Experimental results show that the parallel algorithm is able to reduce the compression time and achieve a high speed-up without changing the compression ratio and the quality of the decompressed image. A scalability test was also performed, and the results show that this parallel algorithm is scalable.

Grey video compression methods using fractals

The authors' experience in the treatment of grey video compression using fractals is summarized and compared with other research in the same field. Experience with parallel and distributed computing is also discussed.

Character-angle based video annotation

A video annotation system includes clips organization, feature description and pattern determination. This paper aims to present a system for basketball zone-defence detection. Particularly, a character-angle based descriptor for feature description is proposed. The well-performed experimental results in basketball zone-defence detection demonstrate that it is robust for both simulations and real-life cases, with less sensitivity to the distribution caused by local translation of subprime defenders. Such a framework can be easily applied to other team-work sports.

Temporal pattern recognition in video clips detection

Temporal representation and reasoning plays an important role in Data Mining and Knowledge Discovery, particularly, in mining and recognizing patterns with rich temporal information. Based on a formal characterization of time-series and state-sequences, this paper presents the computational technique and algorithm for matching state-based temporal patterns. As a case study of real-life applications, zone-defense pattern recognition in basketball games is specially examined as an illustrating example. Experimental results demonstrate that it provides a formal and comprehensive temporal ontology for research and applications in video events detection.

"Practise what we preach": a social constructivist approach to blended learning

This presentation reports on the formal evaluation, through questionnaires, of a new Level 1 undergraduate course, for 130 student teachers, that uses blended learning. The course design seeks to radicalise the department’s approach to teaching, learning and assessment and use students as change agents. Its structure and content, model social constructivist approaches to learning. Building on the student’s experiences of and, reflections on, previous learning, promotes further learning through the support of “able others” (Vygotsky 1978), facilitating and nurturing a secure community of practice for students new to higher education. The course’s design incorporates individual, paired, small and large group activities and exploits online video, audio and text materials. Course units begin and end with face-to-face tutor-led activities. Online elements, including discussions and formative submissions, are tutor-mediated. Students work together face-to-face and online to read articles, write reflections, develop presentations, research and share experiences and resources. Summative joint assignments and peer assessments emphasise the value of collaboration and teamwork for academic, personal and professional development. Initial informal findings are positive, indicating that students have engaged readily with course content and structure, with few reporting difficulties accessing or using technology. Students have welcomed the opportunity to work together to tackle readings in a new genre, pilot presentation skills and receive and give constructive feedback to peers. Course tutors have indicated that depth and quality of study are evident, with regular online formative submissions enabling tutors to identify and engage directly with student’s needs, provide feedback and develop appropriately designed distance and face-to-face teaching materials. Pastoral tutors have indicated that students have reported non-engagement of peers, leading to the rapid application of academic or personal support. Outcomes of the formal evaluation will inform the development of Level 2 and 3 courses and influence the department’s use of blended learning.

Can the use of supplementary video and audio materials support student understanding of 3D animation? Some results, analysis and conclusions

A project within a computing department at the University of Greenwich, has been carried out to identify whether podcasting can be used to help understanding and learning of a subject (3D Animation). We know that the benefits of podcasting in education (HE) can be justified, [1]; [2]; [3]; [4]; [5]; [6] and that some success has been proven, but this paper aims to report the results of a term-long project that provided podcast materials for students to help support their learning using Xserve and Podcast Producer technology. Findings in a previous study [6] identified podcasting as a way to diversify learning and provde a more personalised learning experience for students, as well as being able to provide access to a greater mix of learning styles [7]. Finally this paper aims to present the method of capture and distribution, the methodologies of the study, analysis of results, and conclusions that relate to podcasting and enhanced supported learning.

A revised classification for direct tooth-colored restorative materials

Composite resins and glass-ionomer cements were introduced to dentistry in the 1960s and 1970s, respectively. Since then, there has been a series of modifications to both materials as well as the development other groups claiming intermediate characteristics between the two. The result is a confusion of materials leading to selection problems. While both materials are tooth-colored, there is a considerable difference in their properties, and it is important that each is used in the appropriate situation. Composite resin materials are esthetic and now show acceptable physical strength and wear resistance. However, they are hydrophobic, and therefore more difficult to handle in the oral environment, and cannot support ion migration. Also, the problems of gaining long-term adhesion to dentin have yet to be overcome. On the other hand, glass ionomers are water-based and therefore have the potential for ion migration, both inward and outward from the restoration, leading to a number of advantages. However, they lack the physical properties required for use in load-bearing areas. A logical classification designed to differentiate the materials was first published by McLean et al in 1994, but in the last 15 years, both types of material have undergone further research and modification. This paper is designed to bring the classification up to date so that the operator can make a suitable, evidence-based, choice when selecting a material for any given situation.