The Application of Metadata Standards to Multimedia in Museums

This paper first describes the application of a multi-level indexing approach, based on Dublin Core extensions and the Resource Description Framework (RDF), to a typical museum video. The advantages and disadvantages of this approach are discussed in the context of the requirements of the proposed MPEG-7 ("Multimedia Content Description Interface") standard. The work on SMIL (Synchronized Multimedia Integration Language) by the W3C SYMM working group is then described. Suggestions for how this work can be applied to video metadata are made. Finally a hybrid approach is proposed based on the combined use of Dublin Core and the currently undefined MPEG-7 standard within the RDF which will provide a solution to the problem of satisfying widely differing user requirements

Feedback-Based Gameplay Metrics and Gameplay Performance Segmentation: An audio-visual approach for assessing player experience.

Gameplay metrics is a method and approach that is growing in popularity amongst the game studies research community for its capacity to assess players’ engagement with game systems. Yet, little has been done, to date, to quantify players’ responses to feedback employed by games that conveys information to players, i.e., their audio-visual streams. The present thesis introduces a novel approach to player experience assessment - termed feedback-based gameplay metrics - which seeks to gather gameplay metrics from the audio-visual feedback streams presented to the player during play. So far, gameplay metrics - quantitative data about a game state and the player's interaction with the game system - are directly logged via the game's source code. The need to utilise source code restricts the range of games that researchers can analyse. By using computer science algorithms for audio-visual processing, yet to be employed for processing gameplay footage, the present thesis seeks to extract similar metrics through the audio-visual streams, thus circumventing the need for access to, whilst also proposing a method that focuses on describing the way gameplay information is broadcast to the player during play. In order to operationalise feedback-based gameplay metrics, the present thesis introduces the concept of gameplay performance segmentation which describes how coherent segments of play can be identified and extracted from lengthy game play sessions. Moreover, in order to both contextualise the method for processing metrics and provide a conceptual framework for analysing the results of a feedback-based gameplay metric segmentation, a multi-layered architecture based on five gameplay concepts (system, game world instance, spatial-temporal, degree of freedom and interaction) is also introduced. Finally, based on data gathered from game play sessions with participants, the present thesis discusses the validity of feedback-based gameplay metrics, gameplay performance segmentation and the multi-layered architecture. A software system has also been specifically developed to produce gameplay summaries based on feedback-based gameplay metrics, and examples of summaries (based on several games) are presented and analysed. The present thesis also demonstrates that feedback-based gameplay metrics can be conjointly analysed with other forms of data (such as biometry) in order to build a more complete picture of game play experience. Feedback based game-play metrics constitutes a post-processing approach that allows the researcher or analyst to explore the data however they wish and as many times as they wish. The method is also able to process any audio-visual file, and can therefore process material from a range of audio-visual sources. This novel methodology brings together game studies and computer sciences by extending the range of games that can now be researched but also to provide a viable solution accounting for the exact way players experience games

Automatic indexing of video content via the detection of semantic events

The number, and size, of digital video databases is continuously growing. Unfortunately, most, if not all, of the video content in these databases is stored without any sort of indexing or analysis and without any associated metadata. If any of the videos do have metadata, then it is usually the result of some manual annotation process rather than any automatic indexing. Thus, locating clips and browsing content is difficult, time consuming and generally inefficient. The task of automatically indexing movies is particularly difficult given their innovative creation process and the individual style of many film makers. However, there are a number of underlying film grammar conventions that are universally followed, from a Hollywood blockbuster to an underground movie with a limited budget. These conventions dictate many elements of film making such as camera placement and editing. By examining the use of these conventions it is possible to extract information about the events in a movie. This research aims to provide an approach that creates an indexed version of a movie to facilitate ease of browsing and efficient retrieval. In order to achieve this aim, all of the relevant events contained within a movie are detected and classified into a predefined index. The event detection process involves examining the underlying structure of a movie and utilising audiovisual analysis techniques, supported by machine learning algorithms, to extract information based on this structure. The result is an indexed movie that can be presented to users for browsing/retrieval of relevant events, as well as supporting user specified searching. Extensive evaluation of the indexing approach is carried out. This evaluation indicates efficient performance of the event detection and retrieval system, and also highlights the subjective nature of video content

Digital tools in media studies: analysis and research. An overview

Digital tools are increasingly used in media studies, opening up new perspectives for research and analysis, while creating new problems at the same time. In this volume, international media scholars and computer scientists present their projects, varying from powerful film-historical databases to automatic video analysis software, discussing their application of digital tools and reporting on their results. This book is the first publication of its kind and a helpful guide to both media scholars and computer scientists who intend to use digital tools in their research, providing information on applications, standards, and problems

Digital Tools in Media Studies

Digital tools are increasingly used in media studies, opening up new perspectives for research and analysis, while creating new problems at the same time. In this volume, international media scholars and computer scientists present their projects, varying from powerful film-historical databases to automatic video analysis software, discussing their application of digital tools and reporting on their results. This book is the first publication of its kind and a helpful guide to both media scholars and computer scientists who intend to use digital tools in their research, providing information on applications, standards, and problems

Remember the medium! : film, medium specificity, and response-dependence

Medium specificity is a theory, or rather a cluster of arguments, in aesthetics that rests on the idea that media are the physical material that makes up artworks, and that this material contains specific and unique features capable of 1) differentiating media from one another, and 2) determining the aesthetic potential and goals of each medium. As such, medium specificity is essential for aestheticians interested in matters of aesthetic ontology and value. However, as Noël Carroll has vehemently and convincingly argued, the theory of medium specificity is inherently flawed and its many applications in art history ill-motivated. Famously, he concluded that we should ‘forget the medium’ entirely. In this thesis, I reject his conclusion and argue that reconstructing a theory of medium specificity, while taking Carroll’s objections into account, is possible. To do so, I offer a reconceptualization of the main theoretical components of medium specificity and ground this new theory in empirical research. I first redefine the medium not as the physical material that makes up artworks but as sets of practices – not the material itself but how one uses the material. I then show that what makes media specific and unique is not certain physical features, but the human responses, which can be empirically investigated, to the combination of practices that constitute media. This relation is one of response-dependence, albeit of a novel kind, which I develop by appealing to social metaphysics. The resulting theory is more complex but also much more flexible and fine-grained than the original and provides insight into a variety of current aesthetic theories

“How Short is a Piece of String?”: An Investigation into the Impact of Text Length on Short-Text Classification Accuracy

The recent increase in the widespread use of short messages, for example micro-blogs or SMS communications, has created an opportunity to harvest a vast amount of information through machine-based classification. However, traditional classification methods have failed to produce accuracies comparable to those obtained from similar classification of longer texts. Several approaches have been employed to extend traditional methods to overcome this problem, including the enhancement of the original texts through the construction of associations with external data enrichment sources, ranging from thesauri and semantic nets such as Wordnet, to pre-built online taxonomies such as Wikipedia. Other avenues of investigation have used more formal extensions such as Latent Semantic Analysis (LSA) to extend or replace the more basic, traditional, methods better suited to classification of longer texts. This work examines the changes in classification accuracy of a small selection of classification methods using a variety of enhancement methods, as target text length decreases. The experimental data used is a corpus of micro-blog (twitter) posts obtained from the ‘Sentiment140’1 sentiment classification and analysis project run by Stanford University and described by Go, Bhayani and Huang (2009), which has been split into sub-corpora differentiated by text length

Film as Embodied Art

How do the visuals of Kubrick’s work convey complex concepts and abstractions without the traditional reliance on words? And how does the pure instrumental music in his films express meaning when music, in essence, is an abstract art form? Drawing on state-of-the-art research in embodied cognitive science, this book sets out to explore these questions by revealing Kubrick as a genuine conceptual artist, a filmmaker who perhaps more than any other director, uses all the non-verbal resources of filmmaking in such a controlled and dense manner as to elicit the bodily structures necessary to achieve a level of conceptual understanding