8,797 research outputs found

    Combining face detection and novelty to identify important events in a visual lifelog

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    The SenseCam is a passively capturing wearable camera, worn around the neck and takes an average of almost 2,000 images per day, which equates to over 650,000 images per year. It is used to create a personal lifelog or visual recording of the wearer’s life and generates information which can be helpful as a human memory aid. For such a large amount of visual information to be of any use, it is accepted that it should be structured into “events”, of which there are about 8,000 in a wearer’s average year. In automatically segmenting SenseCam images into events, it is desirable to automatically emphasise more important events and decrease the emphasis on mundane/routine events. This paper introduces the concept of novelty to help determine the importance of events in a lifelog. By combining novelty with face-to-face conversation detection, our system improves on previous approaches. In our experiments we use a large set of lifelog images, a total of 288,479 images collected by 6 users over a time period of one month each

    Intelligent image processing techniques for structuring a visual diary

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    The SenseCam is a small wearable personal device which automatically captures up to 3,500 images per day. This yields a very large personal collection of images or in a sense, a diary of a person's day. Over one million images will need to be stored each year, therefore intelligent techniques are necessary for the effective searching and browsing of this image collection for important or significant events in a person's life, and one of the issues is how to detect and then relate similar events in a lifetime. This is necessary in order to detect unusual or once-off events, as well as determining routine activities. This poster will present the various sources of data that can be collected with a SenseCam device, and also other sources that can be collected to compliment the SenseCam data sources. Different forms of image processing that can be carried out on this large set of images will be detailed, specifically how to detect what images belong to individual events, and also how similar various events are to each other. There will be hundreds of thousands of images of everyday routines; as a result more memorable events are quite likely to be significantly different to other normal reoccurring events

    Structuring and augmenting a visual personal diary

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    This paper refers to research in the domain of visual lifelogging, whereby individuals capture much of their lives using digital cameras. The potential benefits of lifelogging include: applications to review tourist trips, memory aid applications, learning assistants, etc. The SenseCam, developed by Microsoft Research in Cambridge, UK, is a small wearable device which incorporates a digital camera and onboard sensors (motion, ambient temperature, light level, and passive infrared to detect presence of people). There exists a number of challenges in managing the vast quantities of data generated by lifelogging devices such as the SenseCam. Our work concentrates on the following areas withing visual lifelogging: Segmenting sequences of images into events (e.g. breakfast, at meeting); retrieving similar events (what other times was I at the park?); determining most important events (meeting an old friend is more important than breakfast); selection of ideal keyframe to provide an event summary; and augmenting lifeLog events with images taken by millions of users from "Web 2.0" websites (show me other pictures of the Statue of Liberty to augment my own lifelog images)

    Organising a large quantity of lifelog images

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    Preliminary research indicates that a visual recording of one’s activities may be beneficial for sufferers of neurodegenerative diseases. However there exists a number of challenges in managing the vast quantities of data generated by lifelogging devices such as the SenseCam. Our work concentrates on the following areas within visual lifelogging: Segmenting sequences of images into events (e.g. breakfast, at meeting); retrieving similar events (“what other times was I at the park?”); determining most important events (meeting an old friend is more important than breakfast); selection of ideal keyframe to provide an event summary; and augmenting lifeLog events with images taken by millions of users from ‘Web 2.0’ websites (“show me other pictures of the Statue of Liberty to augment my own lifelog images”)

    A very modern professional: the case of the IT service support worker

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    The IT profession has retained a reputation as a ‘privileged area of the labour market’ (Webster, 2005, p.4; Bannerji, 2011). Workers practicing IT skills have been at the forefront of the competitive drive for innovation and efficiency gains promoted by a neoliberal enterprise ideology (Blackler et al, 2003). In the last two decades, as systems thinking (e.g. Ackoff, 1999) and customer-centric practices (e.g. Levitt, 2006) have converged in a globally powerful IT service management (ITSM) ‘best practice’ discourse (Trusson et al, 2013), the IT service support worker has emerged to be a worker-type of considerable socio-economic importance. Aside from keeping organizational information systems operative, when such systems fail these workers are called upon to rapidly restore the systems and thus head-off any negative commercial or political consequences. Yet these workers are acknowledged only as objectified resources within the ITSM ‘best practice’ literature (e.g. Taylor, Iqbal and Nieves, 2007) and largely overlooked as a distinctive contemporary worker-type within academic discourse. This paper, through analysis of salary data and qualitative data collected for a multiple case study research project, considers the extent to which these workers might be conceived of as being ‘professionals’. The project approached the conceptual study of these workers through three lenses. This paper focuses on the project’s consideration of them as rationalised information systems assets within ‘best practice’ ITSM theory. It also draws upon our considerations of them as knowledge workers and service workers. We firstly situate the IT service support worker within a broader model of IT workers comprising four overlapping groupings: managers, developers, technical specialists and IT service support workers. Three types of IT service support worker are identified: first-line workers who routinely escalate work; second-line workers; and ‘expert’ single-line workers. With reference to close associations made with call centre workers (e.g. Murphy, 2011) the status of IT service support workers is explored through analysis of: (i) salary data taken from the ITJOBSWATCH website; and (ii) observational and interview data collected in the field. From this we challenge the veracity of the notion that the whole occupational field of IT might be termed a profession concurrently with the notion that a profession implies work of high status. Secondly, the paper explores two forces that might be associated with the professionalization of IT as an occupation: (i) rationalisation of the field (here promoted by the British Computer Society); and (ii) formalisation of IT theoretical/vocational education. A tension is identified, with those IT service support workers whose work is least disposed to rationalisation and whose complex ‘stocks of knowledge’ (Schutz, 1953) have been acquired through time-spent practice laying claim to greater IT professional status. Thirdly, consideration is given to individuals’ personal career orientations: occupational, organizational and customer-centric (Kinnie and Swart, 2012). We find that whilst organizations expect IT service support workers to be orientated towards serving the interests of the organization and its clients, the most individualistically professional tend towards being occupationally orientated, enthusiastically (re)developing their skills to counter skills obsolescence in an evolving technological arena (Sennett, 2006)

    Extremal Quantum Correlations and Cryptographic Security

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    We investigate a fundamental property of device independent security in quantum cryptography by characterizing probability distributions which are necessarily independent of the measurement results of any eavesdropper. We show that probability distributions that are secure in this sense are exactly the extremal quantum probability distributions. This allows us to give a characterization of security in algebraic terms. We apply the method to common examples for two-party as well as multi-party setups and present a scheme for verifying security of probability distributions with two parties, two measurement settings, and two outcomes.Comment: 7 pages, 2 figures, revised version, accepted for publication in Phys. Rev. Let

    Video shot boundary detection: seven years of TRECVid activity

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    Shot boundary detection (SBD) is the process of automatically detecting the boundaries between shots in video. It is a problem which has attracted much attention since video became available in digital form as it is an essential pre-processing step to almost all video analysis, indexing, summarisation, search, and other content-based operations. Automatic SBD was one of the tracks of activity within the annual TRECVid benchmarking exercise, each year from 2001 to 2007 inclusive. Over those seven years we have seen 57 different research groups from across the world work to determine the best approaches to SBD while using a common dataset and common scoring metrics. In this paper we present an overview of the TRECVid shot boundary detection task, a high-level overview of the most significant of the approaches taken, and a comparison of performances, focussing on one year (2005) as an example

    Mild acetabular dysplasia and risk of osteoarthritis of the hip : a case-control study

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    Objective To determine whether mild variation in acetabular depth (AD) and shape is a risk factor for osteoarthritis (OA) of the hip. Methods The unaffected contralateral hip of patients with unilateral hip OA was compared with hips of asymptomatic controls without hip OA, derived from the Nottingham Genetics Osteoarthritis and Lifestyle case–control study. Standardised anteroposterior x-rays of the pelvis were used to measure centre edge (CE) angle and AD. Cut-off points for narrow CE angle and shallow AD were calculated from the control group (mean −1.96×SD). The relative risk of hip OA associated with each feature was estimated using OR and 95% CI and adjusted risks were calculated by logistic regression. Results In controls, both the CE angle and the AD were lower in the left hip than in the right hip. The CE angle related to age in both hips, and AD of the right hip was lower in men than in women. The contralateral unaffected hip in patients with unilateral hip OA had a decreased CE angle and AD compared with controls, irrespective of side. The lowest tertile of the CE angle in contralateral hips was associated with an eightfold risk of OA (aOR 8.06, 95% CI 4.87 to 13.35) and the lowest tertile of AD was associated with a 2.5-fold risk of OA (aOR 2.53, 95% CI 1.28 to 5.00). Significant increases in the risk of OA were also found as the CE angle and AD decreased

    Automatically detecting important moments from everyday life using a mobile device

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    This paper proposes a new method to detect important moments in our lives. Our work is motivated by the increase in the quantity of multimedia data, such as videos and photos, which are capturing life experiences into personal archives. Even though such media-rich data suggests visual processing to identify important moments, the oft-mentioned problem of the semantic gap means that users cannot automatically identify or retrieve important moments using visual processing techniques alone. Our approach utilises on-board sensors from mobile devices to automatically identify important moments, as they are happening

    Summarisation & Visualisation of Large Volumes of Time-Series Sensor Data

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    a number of sensors, including an electricity usage sensor supplied by Episensor. This poses our second With the increasing ubiquity of sensor data, challenge, how to summarise an extended period of presenting this data in a meaningful way to electrictiy usage data for a home user. users is a challenge that must be addressed before we can easily deploy real-world sensor network interfaces in the home or workplace. In this paper, we will present one solution to the visualisation of large quantities of sensor data that is easy to understand and yet provides meaningful and intuitive information to a user, even when examining many weeks or months of historical data. We will illustrate this visulalisation technique with two real-world deployments of sensing the person and sensing the home
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