624 resultados para Muti-Modal Biometrics, User Authentication, Fingerprint Recognition, Palm Print Recognition


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This paper presents a robust place recognition algorithm for mobile robots that can be used for planning and navigation tasks. The proposed framework combines nonlinear dimensionality reduction, nonlinear regression under noise, and Bayesian learning to create consistent probabilistic representations of places from images. These generative models are incrementally learnt from very small training sets and used for multi-class place recognition. Recognition can be performed in near real-time and accounts for complexity such as changes in illumination, occlusions, blurring and moving objects. The algorithm was tested with a mobile robot in indoor and outdoor environments with sequences of 1579 and 3820 images, respectively. This framework has several potential applications such as map building, autonomous navigation, search-rescue tasks and context recognition.

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In earlier cultures and societies, hazards and risks to human health were dealt with by methods derived from myth, metaphor and ritual. In modem society however, notions of hazard and risk have been transformed from the level of a folk discourse to that of an expert centred concept (Plough & Krimsky, 1987). With the professionalization of risk and hazard analysis came a preferred framework for decision making based on a range of 'technical' methodologies (Giere, 1991 ). This is especially true for decision processes relating to risk assessment and management, and impact assessment. Such approaches however, often entail narrow technical-based theoretical assumptions about human behaviour and the natural world, and the· methods used. They therefore carry 'in-built' error factors that contribute considerable uncertainty to the results.

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Debates about user-generated content (UGC) often depend on a contrast with its normative opposite, the professionally produced content that is supported and sustained by commercial media businesses or public organisations. UGC is seen to appear within or in opposition to professional media, often as a disruptive, creative, change-making force. Our suggestion is to position UGC not in opposition to professional or "producer media", or in hybridised forms of subjective combination with it (the so-called "pro-sumer" or "pro-am" system), but in relation to different criteria, namely the formal and informal elements in media industries. In this article, we set out a framework for the comparative and historical analysis of UGC systems and their relations with other formal and informal media activity, illustrated with examples ranging from games to talkback radio. We also consider the policy implications that emerge from a historicised reading of UGC as a recurring dynamic within media industries, rather than a manifestation of consumer agency specific to digital cultures.

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Robust facial expression recognition (FER) under occluded face conditions is challenging. It requires robust algorithms of feature extraction and investigations into the effects of different types of occlusion on the recognition performance to gain insight. Previous FER studies in this area have been limited. They have spanned recovery strategies for loss of local texture information and testing limited to only a few types of occlusion and predominantly a matched train-test strategy. This paper proposes a robust approach that employs a Monte Carlo algorithm to extract a set of Gabor based part-face templates from gallery images and converts these templates into template match distance features. The resulting feature vectors are robust to occlusion because occluded parts are covered by some but not all of the random templates. The method is evaluated using facial images with occluded regions around the eyes and the mouth, randomly placed occlusion patches of different sizes, and near-realistic occlusion of eyes with clear and solid glasses. Both matched and mis-matched train and test strategies are adopted to analyze the effects of such occlusion. Overall recognition performance and the performance for each facial expression are investigated. Experimental results on the Cohn-Kanade and JAFFE databases demonstrate the high robustness and fast processing speed of our approach, and provide useful insight into the effects of occlusion on FER. The results on the parameter sensitivity demonstrate a certain level of robustness of the approach to changes in the orientation and scale of Gabor filters, the size of templates, and occlusions ratios. Performance comparisons with previous approaches show that the proposed method is more robust to occlusion with lower reductions in accuracy from occlusion of eyes or mouth.

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Mobile devices are rapidly developing into the primary technology for users to work, socialize, and play in a variety of settings and contexts. Their pervasiveness has provided researchers with the means to investigate innovative solutions to ever more complex user demands. Tools for Mobile Multimedia Programming and Development investigates the use of mobile platforms for research projects, focusing on the development, testing, and evaluation of prototypes rather than final products, which enables researchers to better understand the needs of users through image processing, object recognition, sensor integration, and user interactions. This book benefits researchers and professionals in multiple disciplines who utilize such techniques in the creation of prototypes for mobile devices and applications. This book is part of the Advances in Wireless Technologies and Telecommunication series collection.

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In attempting to build intelligent litigation support tools, we have moved beyond first generation, production rule legal expert systems. Our work integrates rule based and case based reasoning with intelligent information retrieval. When using the case based reasoning methodology, or in our case the specialisation of case based retrieval, we need to be aware of how to retrieve relevant experience. Our research, in the legal domain, specifies an approach to the retrieval problem which relies heavily on an extended object oriented/rule based system architecture that is supplemented with causal background information. We use a distributed agent architecture to help support the reasoning process of lawyers. Our approach to integrating rule based reasoning, case based reasoning and case based retrieval is contrasted to the CABARET and PROLEXS architectures which rely on a centralised blackboard architecture. We discuss in detail how our various cooperating agents interact, and provide examples of the system at work. The IKBALS system uses a specialised induction algorithm to induce rules from cases. These rules are then used as indices during the case based retrieval process. Because we aim to build legal support tools which can be modified to suit various domains rather than single purpose legal expert systems, we focus on principles behind developing legal knowledge based systems. The original domain chosen was theAccident Compensation Act 1989 (Victoria, Australia), which relates to the provision of benefits for employees injured at work. For various reasons, which are indicated in the paper, we changed our domain to that ofCredit Act 1984 (Victoria, Australia). This Act regulates the provision of loans by financial institutions. The rule based part of our system which provides advice on the Credit Act has been commercially developed in conjunction with a legal firm. We indicate how this work has lead to the development of a methodology for constructing rule based legal knowledge based systems. We explain the process of integrating this existing commercial rule based system with the case base reasoning and retrieval architecture.

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For the past decade, at least, varieties of small, hand held networked instruments have appeared on the global scene, selling in record numbers, and being utilized by all manner of persons from the old to the young; children, women, men, the wealthy and the poor and in all countries. Their presences bespeak a radical shift in telecommunications infrastructure and the future of communications. They are particularly visible in urban areas where mobile transmission network infrastructure (3G, 4G, cellular and Wi-Fi) is more established and substantial, options more plentiful, and density of populations more dramatic. These end user products—I phones, cell phones, Blackberries, DSi, DS, IPads, Zooms, and others – of the mobile communications industry are the latest, hottest globalized commodities. At the same time, wirelessness, or the state of being wireless, and therefore capable of taking along one's networks, communicating from unlikely spaces, and navigating with GPS, is a complex social, political and economic communications phenomenon of early 21st century life. This thesis examines the specter of being wireless in cities. It lends the entire idea an experimentally envisioned, historical and planned context wherein personalization of media tools is seen both as a design development of corporate, artistic, and military imagination, as well as a profound social phenomenon enabling new forms of sharing, belonging, and urban community. In doing that it asserts the parameters of a new mobile space which, aside from clear benefits to humankind by way of mobility, has reinscribed numerous categories including gender. Moreover, it posits the recognition of other, more nuanced theoretical spaces for complex readings of gender and gendered use, including some instantiation of the notion of 'network' itself as a cyborgian and gendered social form. Additionally, cities are studied as places where technology is not only quickly popularized, but is connected to larger political interests, such as the reading of data, tracking of information, and the new security culture. In so doing the work has been undertaken as an urban spatial analysis and experimental ethnography, utilizing architectural, feminist, techno-utopian, industrial and theoretical literatures as discursive underpinnings from whence understandings and interpretations of mobile space, the mobile office, networked mobility, and personal media have come, linking the space of cities to specific, pioneering urban public art projects in which voice, texting and MMS have been utilized in expressions of ubiquitous networks and urban history. Through numerous examples of techno art, the thesis discusses the 'wireless city' as an emerging cultural, socially constructed economic and spatial entity, both conceived and formed through historic processes of urbanization.

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Traditional HCI design and evaluation methods merely focus on functional and usability aspects of a product. Although these aspects are important, they do not guarantee product’s success, especially the consumer product. Many consumer products are now part of user’s everyday activities – that support fun, pleasure, entertainment, etc. Secondly, in today’s consumer market many of the products have become similar in terms of their technology, functionality, price and quality. In response, many companies have started designing products with added emotional and experiential values. This has challenged designer’s to explore and visualize directions in product design field that could evoke intended and desired experiences amongst its users. Subjective product qualities such as fun, pleasure, entertainment, etc. are not the part of a product, but they are better thought of as the outcome of user’s interaction with the product...

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Faunal vocalisations are vital indicators for environmental change and faunal vocalisation analysis can provide information for answering ecological questions. Therefore, automated species recognition in environmental recordings has become a critical research area. This thesis presents an automated species recognition approach named Timed and Probabilistic Automata. A small lexicon for describing animal calls is defined, six algorithms for acoustic component detection are developed, and a series of species recognisers are built and evaluated.The presented automated species recognition approach yields significant improvement on the analysis performance over a real world dataset, and may be transferred to commercial software in the future.

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Accurate and detailed measurement of an individual's physical activity is a key requirement for helping researchers understand the relationship between physical activity and health. Accelerometers have become the method of choice for measuring physical activity due to their small size, low cost, convenience and their ability to provide objective information about physical activity. However, interpreting accelerometer data once it has been collected can be challenging. In this work, we applied machine learning algorithms to the task of physical activity recognition from triaxial accelerometer data. We employed a simple but effective approach of dividing the accelerometer data into short non-overlapping windows, converting each window into a feature vector, and treating each feature vector as an i.i.d training instance for a supervised learning algorithm. In addition, we improved on this simple approach with a multi-scale ensemble method that did not need to commit to a single window size and was able to leverage the fact that physical activities produced time series with repetitive patterns and discriminative features for physical activity occurred at different temporal scales.

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The ability to identify and assess user engagement with transmedia productions is vital to the success of individual projects and the sustainability of this mode of media production as a whole. It is essential that industry players have access to tools and methodologies that offer the most complete and accurate picture of how audiences/users engage with their productions and which assets generate the most valuable returns of investment. Drawing upon research conducted with Hoodlum Entertainment, a Brisbane-based transmedia producer, this chapter outlines an initial assessment of the way engagement tends to be understood, why standard web analytics tools are ill-suited to measuring it, how a customised tool could offer solutions, and why this question of measuring engagement is so vital to the future of transmedia as a sustainable industry.

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PURPOSE To investigate changes in the characteristics of the corneal optics, total optics, anterior biometrics and axial length of the eye during a near task, in downward gaze, over 10 min. METHODS Ten emmetropes (mean - 0.14 ± 0.24 DS) and 10 myopes (mean - 2.26 ± 1.42 DS) aged from 18 to 30 years were recruited. To measure ocular biometrics and corneal topography in downward gaze, an optical biometer (Lenstar LS900) and a rotating Scheimpflug camera (Pentacam HR) were inclined on a custom built, height and tilt adjustable table. The total optics of the eye were measured in downward gaze with binocular fixation using a modified Shack-Hartmann wavefront sensor. Initially, subjects performed a distance viewing task at primary gaze for 10 min to provide a "wash-out" period for prior visual tasks. A distance task (watching video at 6 m) in downward gaze (25°) and a near task (watching video on a portable LCD screen with 2.5 D accommodation demand) in primary gaze and 25°downward gaze were then carried out, each for 10 min in a randomized order. During measurements, in dichoptic view, a Maltese cross was fixated with the right (untested) eye and the instrument’s fixation target was fixated with the subject’s tested left eye. Immediately after (0 min), 5 and 10 min from the commencement of each trial, measurements of ocular parameters were acquired in downward gaze. RESULTS Axial length exhibited a significant increase with downward gaze and accommodation over time (p<0.05). The greatest axial elongation was observed in downward gaze with 2.5 D accommodation after 10 min (mean change from baseline 23±3 µm). Downward gaze also caused greater changes in anterior chamber depth (ACD) and lens thickness (LT) with accommodation (ACD mean change -163±12µm at 10 min; LT mean change 173±17 µm at 10 min) compared to primary gaze with accommodation (ACD mean change -138±12µm at 10 min; LT mean change 131±15 µm at 10 min). Both corneal power and total ocular power changed by a small but significant amount with downward gaze (p<0.05), resulting in a myopic shift (~0.10 D) in the spherical power of the eye compared with primary gaze. CONCLUSION The axial length, anterior biometrics and ocular refraction change significantly with accommodation in downward gaze as a function of time. These findings provide new insights into the optical and bio-mechanical changes of the eye during typical near tasks.

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Background Wearable monitors are increasingly being used to objectively monitor physical activity in research studies within the field of exercise science. Calibration and validation of these devices are vital to obtaining accurate data. This article is aimed primarily at the physical activity measurement specialist, although the end user who is conducting studies with these devices also may benefit from knowing about this topic. Best Practices Initially, wearable physical activity monitors should undergo unit calibration to ensure interinstrument reliability. The next step is to simultaneously collect both raw signal data (e.g., acceleration) from the wearable monitors and rates of energy expenditure, so that algorithms can be developed to convert the direct signals into energy expenditure. This process should use multiple wearable monitors and a large and diverse subject group and should include a wide range of physical activities commonly performed in daily life (from sedentary to vigorous). Future Directions New methods of calibration now use "pattern recognition" approaches to train the algorithms on various activities, and they provide estimates of energy expenditure that are much better than those previously available with the single-regression approach. Once a method of predicting energy expenditure has been established, the next step is to examine its predictive accuracy by cross-validating it in other populations. In this article, we attempt to summarize the best practices for calibration and validation of wearable physical activity monitors. Finally, we conclude with some ideas for future research ideas that will move the field of physical activity measurement forward.

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Facial expression recognition (FER) has been dramatically developed in recent years, thanks to the advancements in related fields, especially machine learning, image processing and human recognition. Accordingly, the impact and potential usage of automatic FER have been growing in a wide range of applications, including human-computer interaction, robot control and driver state surveillance. However, to date, robust recognition of facial expressions from images and videos is still a challenging task due to the difficulty in accurately extracting the useful emotional features. These features are often represented in different forms, such as static, dynamic, point-based geometric or region-based appearance. Facial movement features, which include feature position and shape changes, are generally caused by the movements of facial elements and muscles during the course of emotional expression. The facial elements, especially key elements, will constantly change their positions when subjects are expressing emotions. As a consequence, the same feature in different images usually has different positions. In some cases, the shape of the feature may also be distorted due to the subtle facial muscle movements. Therefore, for any feature representing a certain emotion, the geometric-based position and appearance-based shape normally changes from one image to another image in image databases, as well as in videos. This kind of movement features represents a rich pool of both static and dynamic characteristics of expressions, which playa critical role for FER. The vast majority of the past work on FER does not take the dynamics of facial expressions into account. Some efforts have been made on capturing and utilizing facial movement features, and almost all of them are static based. These efforts try to adopt either geometric features of the tracked facial points, or appearance difference between holistic facial regions in consequent frames or texture and motion changes in loca- facial regions. Although achieved promising results, these approaches often require accurate location and tracking of facial points, which remains problematic.

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Security protocols are designed in order to provide security properties (goals). They achieve their goals using cryptographic primitives such as key agreement or hash functions. Security analysis tools are used in order to verify whether a security protocol achieves its goals or not. The analysed property by specific purpose tools are predefined properties such as secrecy (confidentiality), authentication or non-repudiation. There are security goals that are defined by the user in systems with security requirements. Analysis of these properties is possible with general purpose analysis tools such as coloured petri nets (CPN). This research analyses two security properties that are defined in a protocol that is based on trusted platform module (TPM). The analysed protocol is proposed by Delaune to use TPM capabilities and secrets in order to open only one secret from two submitted secrets to a recipient