A Genre Classification Plug-in for Data Collection

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Contextual cropping and scaling of TV productions

This is the author's accepted manuscript. The final publication is available at Springer via http://dx.doi.org/10.1007/s11042-011-0804-3. Copyright @ Springer Science+Business Media, LLC 2011.In this paper, an application is presented which automatically adapts SDTV (Standard Definition Television) sports productions to smaller displays through intelligent cropping and scaling. It crops regions of interest of sports productions based on a smart combination of production metadata and systematic video analysis methods. This approach allows a context-based composition of cropped images. It provides a differentiation between the original SD version of the production and the processed one adapted to the requirements for mobile TV. The system has been comprehensively evaluated by comparing the outcome of the proposed method with manually and statically cropped versions, as well as with non-cropped versions. Envisaged is the integration of the tool in post-production and live workflows

ArchivePress: A Really Simple Solution to Archiving Blog Content

ArchivePress is a new technical solution for collecting and archiving content from blogs. Current solutions are commonly based on typical web archiving activities, whereby a crawler is configured to harvest a copy of the blog and return the copy to a web archive. This approach is perfectly acceptable if the requirement is that the site is presented as an integral whole. However, ArchivePress is based upon the premise that blogs are a distinct class of web-based resource, in which the post, not the page, is atomic, and certain properties, such as layouts and colours, are demonstrably superfluous for many (if not most) users. As a result, an approach that builds on the functionality provided by web feeds to capture only selected aspects of the blog offers more potential. This is particularly the case when institutions wish to develop collections of aggregated blog content from a range of different sources. The presentation will describe our research to develop such an approach, including work to define the significant properties of blogs, details of the technical development, and pilot collections against which the tool has been tested

Designing an interface for a digital movie browsing system in the film studies domain

This article explains our work in designing an interface for a digital movie browsing system in the specific application context of film studies. The development of MOVIEBROWSER2 follows some general design guidelines based on an earlier user study with film studies students at Dublin City University. These design guidelines have been used as an input to the MOVIEBROWSER2 system design. The rationale for the interface design decisions has been elaborated. An experiment has been carried out among film studies student, together with a one-semester trial deployment. The results show positive feedback and a better performance in the students’ essay outcome with higher perceived satisfaction level

Intelligent image cropping and scaling

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University, 2011.Nowadays, there exist a huge number of end devices with different screen properties for watching television content, which is either broadcasted or transmitted over the internet. To allow best viewing conditions on each of these devices, different image formats have to be provided by the broadcaster. Producing content for every single format is, however, not applicable by the broadcaster as it is much too laborious and costly. The most obvious solution for providing multiple image formats is to produce one high resolution format and prepare formats of lower resolution from this. One possibility to do this is to simply scale video images to the resolution of the target image format. Two significant drawbacks are the loss of image details through ownscaling and possibly unused image areas due to letter- or pillarboxes. A preferable solution is to find the contextual most important region in the high-resolution format at first and crop this area with an aspect ratio of the target image format afterwards. On the other hand, defining the contextual most important region manually is very time consuming. Trying to apply that to live productions would be nearly impossible. Therefore, some approaches exist that automatically define cropping areas. To do so, they extract visual features, like moving reas in a video, and define regions of interest (ROIs) based on those. ROIs are finally used to define an enclosing cropping area. The extraction of features is done without any knowledge about the type of content. Hence, these approaches are not able to distinguish between features that might be important in a given context and those that are not. The work presented within this thesis tackles the problem of extracting visual features based on prior knowledge about the content. Such knowledge is fed into the system in form of metadata that is available from TV production environments. Based on the extracted features, ROIs are then defined and filtered dependent on the analysed content. As proof-of-concept, this application finally adapts SDTV (Standard Definition Television) sports productions automatically to image formats with lower resolution through intelligent cropping and scaling. If no content information is available, the system can still be applied on any type of content through a default mode. The presented approach is based on the principle of a plug-in system. Each plug-in represents a method for analysing video content information, either on a low level by extracting image features or on a higher level by processing extracted ROIs. The combination of plug-ins is determined by the incoming descriptive production metadata and hence can be adapted to each type of sport individually. The application has been comprehensively evaluated by comparing the results of the system against alternative cropping methods. This evaluation utilised videos which were manually cropped by a professional video editor, statically cropped videos and simply scaled, non-cropped videos. In addition to and apart from purely subjective evaluations, the gaze positions of subjects watching sports videos have been measured and compared to the regions of interest positions extracted by the system

Addressing the Challenges of Assessment and Feedback in Higher Education: A collaborative effort across three UK Universities

Assessment has been identified as one of the major challenges faced by Higher Education Institutions (Whitelock, et al, 2007). As a response to the challenge, in a project funded by the Joint Information Systems Committee (JISC) Open Mentor (OM) was developed as a learning support tool for tutors to help them reflect on the quality of feedback given to their students on assignments submitted electronically. Its development was based on the fundamental theory that there was convincing evidence of systematic connections between different types of tutor comments and the level of attainment in an assignment (Whitelock, et al 2004). OM analyses, filters, and classifies tutor comments through an algorithm based on Bale’s Interaction Process. As a result, tutor’s feedback comments are classified into four categories namely: Positive reactions, Teaching points, Questions and Negative reactions. The feedback provided is analysed against an ideal number of feedback comments that an assignment given a mark of a specific band should have. Reports are provided in OM to support tutors in the task of reflecting on their feedback structure, content and style. The JISC-funded Open Mentor technology transfer (OMtetra) project is continuing the work initiated by the Open University implementing OM at the University of Southampton and King’s College London. OMtetra aims at taking up OM and extending its use by developing the system further and ultimately offering better support to tutors and students in the assessment process. A group of tutors from the University of Southampton and Kings’ College are at present using OM in their teaching and assessment. In this paper, we explore potential improvements to OM in three aspects: user interface, technology implementation and analysis algorithm design. For the user experience aspect suggested additions to OM include the creation of a simple entry form where tutors may validate the results of the analysis of the feedback comments. In addition, enhancements to OM will facilitate uploading of students and modules information into the system. Presently, OM utilises a built-in database of users that needs to be maintained separately from institutional systems. Improvements for this system feature include a more flexible authentication module which would simplify the deployment of the system in new environments and thus promote uptake by a larger number of institutions. In order to reach this goal, the system will be migrated to an open source framework which provides out-of-the-box integration with various authentication systems. The last to improve is the analysis algorithm. Currently, OM classifies tutors’ comments into four categories by applying an underlying text matching algorithm. This method could be improved if tutors are allowed to confirm comments’ classification through the OM interface and a free-text classification algorithm. As the number of users grow, so will the algorithm and analysis process, making it more comprehensive and intelligent as the keywords used during analysis are dynamically expanded. OMtetra is an on-going project with a lot of potential. We believe that the outcomes from the development and trial implementations of OM will contribute highly to the area of assessment in higher education

How to measure musical preference on Facebook? Evidence from a mixed-method data collection

More and more digital data is available for social science analysis. This provides new ways of measuring several concepts. But when we start using new data sources, we have to understand how the new data source could be processed and how it could be analysed effectively. It is especially for Facebook data since there is no established gold standard analysis-framework. However, researchers have in-depth knowledge on how to measure different concepts using survey data. Thus, cross-referencing Facebook data with survey data is a reasonable way to support Facebook data analysis at different decision points. In this paper, we present how music preference could be measured by Facebook data and how survey data could support the selection of main indicators. Based on our results, we provide some general suggestions for Facebook data processing and indicator operationalization.Comment: 35 pages 3 figures, 6 table