Rushes summarization by IRIM consortium: redundancy removal and multi-feature fusion

International audienceIn this paper, we present the first participation of a consortium of French laboratories, IRIM, to the TRECVID 2008 BBC Rushes Summarization task. Our approach resorts to video skimming. We propose two methods to reduce redundancy, as rushes include several takes of scenes. We also take into account low and midlevel semantic features in an ad-hoc fusion method in order to retain only significant content

Understanding user experience of mobile video: Framework, measurement, and optimization

Since users have become the focus of product/service design in last decade, the term User eXperience (UX) has been frequently used in the field of Human-Computer-Interaction (HCI). Research on UX facilitates a better understanding of the various aspects of the user’s interaction with the product or service. Mobile video, as a new and promising service and research field, has attracted great attention. Due to the significance of UX in the success of mobile video (Jordan, 2002), many researchers have centered on this area, examining users’ expectations, motivations, requirements, and usage context. As a result, many influencing factors have been explored (Buchinger, Kriglstein, Brandt & Hlavacs, 2011; Buchinger, Kriglstein & Hlavacs, 2009). However, a general framework for specific mobile video service is lacking for structuring such a great number of factors. To measure user experience of multimedia services such as mobile video, quality of experience (QoE) has recently become a prominent concept. In contrast to the traditionally used concept quality of service (QoS), QoE not only involves objectively measuring the delivered service but also takes into account user’s needs and desires when using the service, emphasizing the user’s overall acceptability on the service. Many QoE metrics are able to estimate the user perceived quality or acceptability of mobile video, but may be not enough accurate for the overall UX prediction due to the complexity of UX. Only a few frameworks of QoE have addressed more aspects of UX for mobile multimedia applications but need be transformed into practical measures. The challenge of optimizing UX remains adaptations to the resource constrains (e.g., network conditions, mobile device capabilities, and heterogeneous usage contexts) as well as meeting complicated user requirements (e.g., usage purposes and personal preferences). In this chapter, we investigate the existing important UX frameworks, compare their similarities and discuss some important features that fit in the mobile video service. Based on the previous research, we propose a simple UX framework for mobile video application by mapping a variety of influencing factors of UX upon a typical mobile video delivery system. Each component and its factors are explored with comprehensive literature reviews. The proposed framework may benefit in user-centred design of mobile video through taking a complete consideration of UX influences and in improvement of mobile videoservice quality by adjusting the values of certain factors to produce a positive user experience. It may also facilitate relative research in the way of locating important issues to study, clarifying research scopes, and setting up proper study procedures. We then review a great deal of research on UX measurement, including QoE metrics and QoE frameworks of mobile multimedia. Finally, we discuss how to achieve an optimal quality of user experience by focusing on the issues of various aspects of UX of mobile video. In the conclusion, we suggest some open issues for future study

Content-based video retrieval: three example systems from TRECVid

The growth in available online video material over the internet is generally combined with user-assigned tags or content description, which is the mechanism by which we then access such video. However, user-assigned tags have limitations for retrieval and often we want access where the content of the video itself is directly matched against a user’s query rather than against some manually assigned surrogate tag. Content-based video retrieval techniques are not yet scalable enough to allow interactive searching on internet-scale, but the techniques are proving robust and effective for smaller collections. In this paper we show 3 exemplar systems which demonstrate the state of the art in interactive, content-based retrieval of video shots, and these three are just three of the more than 20 systems developed for the 2007 iteration of the annual TRECVid benchmarking activity. The contribution of our paper is to show that retrieving from video using content-based methods is now viable, that it works, and that there are many systems which now do this, such as the three outlined herein. These systems, and others can provide effective search on hundreds of hours of video content and are samples of the kind of content-based search functionality we can expect to see on larger video archives when issues of scale are addressed

Common Emotion Modeling in Distinct Medium Analysis and Matching

With the ever growing amount of digital information and multimedia on the World Wide Web and the current trend towards personalizing technology, users find themselves wanting a more intuitive way of finding related information, and not just any information but relevant information that is personal to them. One way to personalize and filter the information is by extracting the mood affectation, allowing the user to search based on current mood. The artificial intelligence field has done extensive research and continues to discover and improve current mood extraction techniques for each distinct medium. This paper will explore how to link and integrate the mood extraction of several distinct mediums— audio, image, and text—by utilizing a common emotion model that is customizable to the user. This project will allow the user to provide an input medium and find a matching output of a different medium based on default settings or user customization

Software agents in music and sound art research/creative work: Current state and a possible direction

Composers, musicians and computer scientists have begun to use software-based agents to create music and sound art in both linear and non-linear (non-predetermined form and/or content) idioms, with some robust approaches now drawing on various disciplines. This paper surveys recent work: agent technology is first introduced, a theoretical framework for its use in creating music/sound art works put forward, and an overview of common approaches then given. Identifying areas of neglect in recent research, a possible direction for further work is then briefly explored. Finally, a vision for a new hybrid model that integrates non-linear, generative, conversational and affective perspectives on interactivity is proposed

Spatio-Temporal Pyramid Matching for Sports Videos

In this paper, we address the problem of querying video shots based on content-based matching. Our proposed system automatically partitions a video stream into video shots that maintain continuous movements of objects. Finding video shots of the same category is not an easy task because objects in a video shot change their locations over time. Our spatio-temporal pyramid matching (STPM) is the modified spatial pyramid matching (SPM) [15], which considers temporal information in conjunction with spatial locations to match objects in video shots. In addition, we model the mathematical condition in which temporal information contributes to match video shots. In order to improve the matching performance, dynamic features including movements of objects are considered in addition to static features such as edges of objects. In our experiments, several methods based on different feature sets and matching methods are compared, and our spatio-temporal pyramid matching performed better than existing methods in video matching for sports videos. 1

Mobile Learning Content Authoring Tools (MLCATs): A Systematic Review

Mobile learning is currently receiving a lot of attention within the education arena, particularly within electronic learning. This is attributed to the increasing mobile penetration rates and the subsequent increases in university student enrolments. Mobile Learning environments are supported by a number of crucial services such as content creation which require an authoring tool. The last decade or so has witnessed increased attention to tools for authoring mobile learning content for education. This can be seen from the vast number of conference and journal publications devoted to the topic. Therefore, the goal of this paper is to review works that were published, suggest a new classification framework and explore each of the classification features. This paper is based on a systematic review of mobile learning content authoring tools (MLCATs) from 2000 to 2009. The framework is developed based on a number of dimensions such as system type, development context, Tools and Technologies used, tool availability, ICTD relation, support for standards, learning style support, media supported and tool purpose. This paper provides a means for researchers to extract assertions and several important lessons for the choice and implementation of MLCATs

A Review of Information Systems Research on Online Social Networks

Over the last decade, online social networks have evolved into a global mainstream medium with increasing social, organizational, and economic impact. This paper provides a structured overview of Information Systems research on this outstanding techno-social phenomenon of the 21st century via a structured literature review. Based on our search in information systems journals and conference proceedings that resulted in 510 papers, we carve out and assess the knowledge and the research fields that have been predominantly addressed and impacted by the information systems research community so far. Moreover, we identify research gaps that future research should address. We analyze how the academic discussion on online social networks developed in the information systems literature over time, which publication outlets are most receptive to research on online social networks, which research areas have already been covered by information systems research on online social networks, and what potential future research areas exist that have not been covered by information systems research yet. We hope that our results will stimulate and guide future research in this field