480 research outputs found

    A novel user-centered design for personalized video summarization

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    In the past, several automatic video summarization systems had been proposed to generate video summary. However, a generic video summary that is generated based only on audio, visual and textual saliencies will not satisfy every user. This paper proposes a novel system for generating semantically meaningful personalized video summaries, which are tailored to the individual user's preferences over video semantics. Each video shot is represented using a semantic multinomial which is a vector of posterior semantic concept probabilities. The proposed system stitches video summary based on summary time span and top-ranked shots that are semantically relevant to the user's preferences. The proposed summarization system is evaluated using both quantitative and subjective evaluation metrics. The experimental results on the performance of the proposed video summarization system are encouraging

    The Evolution of First Person Vision Methods: A Survey

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    The emergence of new wearable technologies such as action cameras and smart-glasses has increased the interest of computer vision scientists in the First Person perspective. Nowadays, this field is attracting attention and investments of companies aiming to develop commercial devices with First Person Vision recording capabilities. Due to this interest, an increasing demand of methods to process these videos, possibly in real-time, is expected. Current approaches present a particular combinations of different image features and quantitative methods to accomplish specific objectives like object detection, activity recognition, user machine interaction and so on. This paper summarizes the evolution of the state of the art in First Person Vision video analysis between 1997 and 2014, highlighting, among others, most commonly used features, methods, challenges and opportunities within the field.Comment: First Person Vision, Egocentric Vision, Wearable Devices, Smart Glasses, Computer Vision, Video Analytics, Human-machine Interactio

    Developing Adaptive and Personalized Mobile Applications: A Framework and Design Issues

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    The rapid growth of mobile technology has expedited ubiquitous information access via handheld devices. However, the fundamental natures of mobile information systems are different from those of desktop applications in terms of purpose of use, device features, communication networks, and working environments. This poses various challenges to mobile information systems on how to deliver and present multimedia content in an effective and adaptive manner. One of the major challenges is to deliver personalized information to the right person in a preferred format based on the changing environment. This paper proposes an innovative framework for developing mobile applications that deliver personalized, context-aware, and adaptive content to mobile users. The framework consists of four major components: information selection, content analysis, media transcoding, and customized presentation. It can be applied to a variety of mobile applications such as mobile web, news alert services, and mobile commerce

    Extending the Bayesian classifier to a context-aware recommender system for mobile devices

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    Mobile devices that are capable of playing Internet videos have become wide-spread in recent years. Because of the enormous offer of video content, the lack of sufficient presentation space on the screen, and the laborious navigation on mobile devices, the video consumption process becomes more complicated for the end-user. To handle this problem, people need new instruments to assist with the hunting, filtering and selection process. We developed a methodology for mobile devices that makes the huge content sources more manageable by creating a user profile and personalizing the offer. This paper reports the structure of the user profile, the user interaction mechanism, and the recommendation algorithm, an improved version of the Bayesian classifier that incorporates aspects of the consumption context (like time, location, and mood of the user) to make the suggestions more accurate

    Enabling pervasive computing with smart phones

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    The authors discuss their experience with a number of mobile telephony projects carried out in the context of the European Union Information Society Technologies research program, which aims to develop mobile information services. They identify areas where use of smart phones can enable pervasive computing and offer practical advice in terms of lessons learned. To this end, they first look at the mobile telephone as * the end point of a mobile information service,* the control device for ubiquitous systems management and configuration,* the networking hub for personal and body area networks, and* identification tokens.They conclude with a discussion of business and practical issues that play a significant role in deploying research systems in realistic situations

    Adaptive Content Delivery Over the Mobile Web

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    Verfahren zur Inhaltsadaption von Darstellungselementen

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    Dieser Bericht gibt einen Überblick über bekannte Verfahren und Technologien zur automatischen Adaption von Darstellungselementen für mobile Endgeräte, wobei der Schwerpunkt bei Verfahren zur Adaption von Bildern, Videos, Webseiten und Audiodateien liegt. Ziel ist es, basierend auf den Eigenschaften des Endgerätes und den Interaktionsmöglichkeiten, geeignete Darstellungsformate automatisch abzuleiten. Als mögliche Endgeräte werden Mobiltelefone, PDAs, Tablet PCs und Notebook PCs betrachtet. Ein guter Adaptionsalgorithmus sollte eine computergestützte Umformatierung von nur einmal bereit gestellten Inhalten für die verschiedenen Formfaktoren, Auflösungen, Bildschirmgrößen, Interaktionstechniken (Maus, Stift, Touch-Screen usw.) und Netzbandbreiten unterstützen

    Investigation Report on Universal Multimedia Access

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    Universal Multimedia Access (UMA) refers to the ability to access by any user to the desired multimedia content(s) over any type of network with any device from anywhere and anytime. UMA is a key framework for multimedia content delivery service using metadata. This investigation report analyzes the state-of-the-art technologies in UMA and tries to identify the key issues of UMA. The state-of-the-art in multimedia content adaptation, an overview of the standards that supports the UMA framework, potential privacy problems in UMA systems and some new UMA applications are presented in this report. This report also provides challenges that still remain to be resolved in UMA to make clear the potential key problems in UMA and determine which ones to solve

    Technology in the 21st Century: New Challenges and Opportunities

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    Although big data, big data analytics (BDA) and business intelligence have attracted growing attention of both academics and practitioners, a lack of clarity persists about how BDA has been applied in business and management domains. In reflecting on Professor Ayre's contributions, we want to extend his ideas on technological change by incorporating the discourses around big data, BDA and business intelligence. With this in mind, we integrate the burgeoning but disjointed streams of research on big data, BDA and business intelligence to develop unified frameworks. Our review takes on both technical and managerial perspectives to explore the complex nature of big data, techniques in big data analytics and utilisation of big data in business and management community. The advanced analytics techniques appear pivotal in bridging big data and business intelligence. The study of advanced analytics techniques and their applications in big data analytics led to identification of promising avenues for future research
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