Event Based Media Indexing

Multimedia data, being multidimensional by its nature, requires appropriate approaches for its organizing and sorting. The growing number of sensors for capturing the environmental conditions in the moment of media creation enriches data with context-awareness. This unveils enormous potential for eventcentred multimedia processing paradigm. The essence of this paradigm lies in using events as the primary means for multimedia integration, indexing and management. Events have the ability to semantically encode relationships of different informational modalities. These modalities can include, but are not limited to: time, space, involved agents and objects. As a consequence, media processing based on events facilitates information perception by humans. This, in turn, decreases the individual’s effort for annotation and organization processes. Moreover events can be used for reconstruction of missing data and for information enrichment. The spatio-temporal component of events is a key to contextual analysis. A variety of techniques have recently been presented to leverage contextual information for event-based analysis in multimedia. The content-based approach has demonstrated its weakness in the field of event analysis, especially for the event detection task. However content-based media analysis is important for object detection and recognition and can therefore play a role which is complementary to that of event-driven context recognition. The main contribution of the thesis lies in the investigation of a new eventbased paradigm for multimedia integration, indexing and management. In this dissertation we propose i) a novel model for event based multimedia representation, ii) a robust approach for mining events from multimedia and iii) exploitation of detected events for data reconstruction and knowledge enrichment

Collections : adapting the display of personal objects for different audiences

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2000.Includes bibliographical references (leaves 64-68).Although current networked systems and online applications provide new opportunities for displaying and sharing personal information, they do not account for the underlying social contexts that frame such interactions. Existing categorization and management mechanisms for digital content have been designed to focus on the data they handle without much regard for the social circumstances within which their content is shared. As we share large collections of personal information over mediated environments, our tools need to account for the social scenarios that surround our interactions. This thesis presents Collections: an application for the management of digital pictures according to their intended audiences. The goal is to create a graphical interface that supports the creation of fairly complex privacy decisions concerning the display of digital photographs. Simple graphics are used to enable the collector to create a wide range of audience arrangements for her digital photographs. The system allows users to express their preferences in sharing their personal pictures over a disembodied environment such as the Web. The system also introduces an original approach to the presentation interface of photographic collections on the Web: a viewing application that takes into account the viewing history of the photographs and the integration of text comments to images.by Fernanda Bertini Viégas.S.M

Address forms in conversations on social media

The goal of the paper is to present addressing practices characteristic of discourse on social media by analysing two Facebook conversations. As the analysis shows, address forms have several roles including the identification of discourse participants, the evoking of patterns of face-to-face spoken discourse, the expression of emotions, and the increasing or reduction of social distance. In the absence of physical presence, discourse participants engaging in internet-based communication cannot rely on nonverbal channels for the construal of social relationships, thus more significance is attached to linguistic devices in general and the patterns specifically marking social relationships in particular. Both conversations (a series of congratulations, and a debate within a Facebook group) feature address forms in a high number and in varied functions. Address forms in congratulatory messages not only construe social relationships but also represent them for the public. In the public debate, addressing practices indicate the convergence or divergence of opinions, and by identifying discourse participants, they also play a role in the delimitation of smaller units within the overall group conversation

Changing Higher Education Learning with Web 2.0 and Open Education Citation, Annotation, and Thematic Coding Appendices

Appendices of citations, annotations and themes for research conducted on four websites: Delicious, Wikipedia, YouTube, and Facebook

Social impact retrieval: measuring author influence on information retrieval

The increased presence of technologies collectively referred to as Web 2.0 mean the entire process of new media production and dissemination has moved away from an authorcentric approach. Casual web users and browsers are increasingly able to play a more active role in the information creation process. This means that the traditional ways in which information sources may be validated and scored must adapt accordingly. In this thesis we propose a new way in which to look at a user's contributions to the network in which they are present, using these interactions to provide a measure of authority and centrality to the user. This measure is then used to attribute an query-independent interest score to each of the contributions the author makes, enabling us to provide other users with relevant information which has been of greatest interest to a community of like-minded users. This is done through the development of two algorithms; AuthorRank and MessageRank. We present two real-world user experiments which focussed around multimedia annotation and browsing systems that we built; these systems were novel in themselves, bringing together video and text browsing, as well as free-text annotation. Using these systems as examples of real-world applications for our approaches, we then look at a larger-scale experiment based on the author and citation networks of a ten year period of the ACM SIGIR conference on information retrieval between 1997-2007. We use the citation context of SIGIR publications as a proxy for annotations, constructing large social networks between authors. Against these networks we show the effectiveness of incorporating user generated content, or annotations, to improve information retrieval

Organising and structuring a visual diary using visual interest point detectors

As wearable cameras become more popular, researchers are increasingly focusing on novel applications to manage the large volume of data these devices produce. One such application is the construction of a Visual Diary from an individual’s photographs. Microsoft’s SenseCam, a device designed to passively record a Visual Diary and cover a typical day of the user wearing the camera, is an example of one such device. The vast quantity of images generated by these devices means that the management and organisation of these collections is not a trivial matter. We believe wearable cameras, such as SenseCam, will become more popular in the future and the management of the volume of data generated by these devices is a key issue. Although there is a significant volume of work in the literature in the object detection and recognition and scene classification fields, there is little work in the area of setting detection. Furthermore, few authors have examined the issues involved in analysing extremely large image collections (like a Visual Diary) gathered over a long period of time. An algorithm developed for setting detection should be capable of clustering images captured at the same real world locations (e.g. in the dining room at home, in front of the computer in the office, in the park, etc.). This requires the selection and implementation of suitable methods to identify visually similar backgrounds in images using their visual features. We present a number of approaches to setting detection based on the extraction of visual interest point detectors from the images. We also analyse the performance of two of the most popular descriptors - Scale Invariant Feature Transform (SIFT) and Speeded Up Robust Features (SURF).We present an implementation of a Visual Diary application and evaluate its performance via a series of user experiments. Finally, we also outline some techniques to allow the Visual Diary to automatically detect new settings, to scale as the image collection continues to grow substantially over time, and to allow the user to generate a personalised summary of their data