"You Tube and I Find" - personalizing multimedia content access

Recent growth in broadband access and proliferation of small personal devices that capture images and videos has led to explosive growth of multimedia content available everywhereVfrom personal disks to the Web. While digital media capture and upload has become nearly universal with newer device technology, there is still a need for better tools and technologies to search large collections of multimedia data and to find and deliver the right content to a user according to her current needs and preferences. A renewed focus on the subjective dimension in the multimedia lifecycle, fromcreation, distribution, to delivery and consumption, is required to address this need beyond what is feasible today. Integration of the subjective aspects of the media itselfVits affective, perceptual, and physiological potential (both intended and achieved), together with those of the users themselves will allow for personalizing the content access, beyond today’s facility. This integration, transforming the traditional multimedia information retrieval (MIR) indexes to more effectively answer specific user needs, will allow a richer degree of personalization predicated on user intention and mode of interaction, relationship to the producer, content of the media, and their history and lifestyle. In this paper, we identify the challenges in achieving this integration, current approaches to interpreting content creation processes, to user modelling and profiling, and to personalized content selection, and we detail future directions. The structure of the paper is as follows: In Section I, we introduce the problem and present some definitions. In Section II, we present a review of the aspects of personalized content and current approaches for the same. Section III discusses the problem of obtaining metadata that is required for personalized media creation and present eMediate as a case study of an integrated media capture environment. Section IV presents the MAGIC system as a case study of capturing effective descriptive data and putting users first in distributed learning delivery. The aspects of modelling the user are presented as a case study in using user’s personality as a way to personalize summaries in Section V. Finally, Section VI concludes the paper with a discussion on the emerging challenges and the open problems

User study for generating personalized summary profiles

Abstract and only some features (e.g., faces, reportage, text, chorus, host, etc.

Video Scouting Demonstration: Smart Content Selection and Recording

Smart video content selection and recording is the best selling feature of the current personal TV receivers like TiVo. These devices operate at the 'IV program level in that they use electronic program guides and user's program personal preferences to help consumers record and watch programs that match their interests. In this Video Scouting demonstration, we present a system that allows for the filtering and retrieving of TV sub-programs based on user's content preferences. The filtering process is realized via real-time video, audio, and transcript analysis. The demonstrator personalizes the TV experience in the areas of celebrity and financial information. The technology can translate into differentiating storage and set-top box product features for finding your favorite actors, most interesting personalized financial news of the day, commercial compaction and enhancement, and content augmentation with other sources of information such as Web pages and encyclopedia. The demonstrator also reflects our active involvement in the MPEG-7 standard (Content Description Interface)

.com User Study for Generating Personalized Summary Profiles

The need for personalized summaries of media content has been driven by the recent and anticipated explosive growth in the media world. In this paper we present a methodology and a supporting user study for generating user profiles and content features that can be used to automatically create personalized summaries of broadcast television content. We determined a mapping, from users ' personality traits measured by commonly available personality tests, to computable video features that such personality traits appear to prefer. Three common personality profiles (Myers-Briggs, Merrill Reed, and Brain.exe) were elicited from 59 subjects, together with their preferred summary of news, music, and talk show videos. A factor analysis between the personality traits and the features in preferred summaries indicated that only some traits (e.g., gender, extraversion, control orientation, intuitiveness, etc.) and only some features (e.g., faces, reportage, text, chorus, host, etc.) had predictive value. The mapping of personality to feature also differed by genre. However, in general, extraverted users tended to prefer directly experienced content, while introverted users preferred content mediated through analysis. A validation user study is in progress. 1

Interface design for MyInfo: A personal news demonstrator combining Web and TV content

Abstract: This paper describes MyInfo, a novel interface for a personal news demonstrator that processes and combines content from TV and the web. We detail our design process from concept generation to focus group exploration to final design. Our design focuses on three issues: (i) ease-of-use, (ii) video summarization, and (iii) news personalization. With a single button press on the remote control, users access specific topics such as weather or traffic. In addition, users can play back personalized news content as a TV show, leaving themselves free to complete other tasks in their homes, while consuming the news