55 resultados para Face representation and recognition


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Significant recent progress has shown ear recognition to be a viable biometric. Good recognition rates have been demonstrated under controlled conditions, using manual registration or with specialised equipment. This paper describes a new technique which improves the robustness of ear registration and recognition, addressing issues of pose variation, background clutter and occlusion. By treating the ear as a planar surface and creating a homography transform using SIFT feature matches, ears can be registered accurately. The feature matches reduce the gallery size and enable a precise ranking using a simple 2D distance algorithm. When applied to the XM2VTS database it gives results comparable to PCA with manual registration. Further analysis on more challenging datasets demonstrates the technique to be robust to background clutter, viewing angles up to +/- 13 degrees and with over 20% occlusion.

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Data registration refers to a series of techniques for matching or bringing similar objects or datasets together into alignment. These techniques enjoy widespread use in a diverse variety of applications, such as video coding, tracking, object and face detection and recognition, surveillance and satellite imaging, medical image analysis and structure from motion. Registration methods are as numerous as their manifold uses, from pixel level and block or feature based methods to Fourier domain methods.

This book is focused on providing algorithms and image and video techniques for registration and quality performance metrics. The authors provide various assessment metrics for measuring registration quality alongside analyses of registration techniques, introducing and explaining both familiar and state-of-the-art registration methodologies used in a variety of targeted applications.

Key features:
- Provides a state-of-the-art review of image and video registration techniques, allowing readers to develop an understanding of how well the techniques perform by using specific quality assessment criteria
- Addresses a range of applications from familiar image and video processing domains to satellite and medical imaging among others, enabling readers to discover novel methodologies with utility in their own research
- Discusses quality evaluation metrics for each application domain with an interdisciplinary approach from different research perspectives

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We describe a protocol for the generation and validation of bacteria microarrays and their application to the study of specific features of the pathogen's surface and interactions with host receptors. Bacteria were directly printed on nitrocellulose-coated glass slides, using either manual or robotic arrayers, and printing quality, immobilization efficiency and stability of the arrays were rigorously controlled by incorporating a fluorescent dye into the bacteria. A panel of wild type and mutant strains of the human pathogen Klebsiella pneumoniae, responsible for nosocomial and community-acquired infections, was selected as model bacteria, and SYTO-13 was used as dye. Fluorescence signals of the printed bacteria were found to exhibit a linear concentration-dependence in the range of 1 x 10(8) to 1 x 10(9) bacteria per ml. Similar results were obtained with Pseudomonas aeruginosa and Acinetobacter baumannii, two other human pathogens. Successful validation of the quality and applicability of the established microarrays was accomplished by testing the capacity of the bacteria array to detect recognition by anti-Klebsiella antibodies and by the complement subcomponent C1q, which binds K. pneumoniae in an antibody-independent manner. The biotin/AlexaFluor-647-streptavidin system was used for monitoring binding, yielding strain-and dose-dependent signals, distinctive for each protein. Furthermore, the potential of the bacteria microarray for investigating specific features, e.g. glycosylation patterns, of the cell surface was confirmed by examining the binding behaviour of a panel of plant lectins with diverse carbohydrate-binding specificities. This and other possible applications of the newly developed arrays, as e.g. screening/evaluation of compounds to identify inhibitors of host-pathogen interactions, make bacteria microarrays a useful and sensitive tool for both basic and applied research in microbiology, biomedicine and biotechnology.

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This paper engages with the varieties of capitalism literature to investigate the employee representation and consultation approaches of liberal market economy multinational companies (MNCs), specifically Australian, British and US MNCs operating in Australia. While the literature would suggest commonality amongst these MNCs, the paper considers whether the evidence points to similarity or variation amongst liberal market headquartered MNCs. The findings contribute to filling a recognized empirical gap on MNC employment relations practice in Australia and to a better understanding of within category varieties of capitalism similarity and variation. Drawing on survey data from MNCs operating in Australia, the results demonstrated that UK-owned MNCs were the least likely to report collective structures of employee representation. Moreover, it was found that Australian MNCs were the most likely to engage in collective forms of employee representation and made less use of direct consultative mechanisms relative to their British and US counterparts. In spite of the concerted individualization of the employment relations domain over previous decades, Australian MNCs appear to have upheld more long-standing national institutional arrangements with respect to engaging with employees on a collective basis. This varies from British and US MNC approaches which denotes that our results display within category deviation in the variety of capitalism liberal market economy typology. Just as Hall and Soskice described their seminal work on liberal market economy (LME) and coordinated market economy (CME) categories as a “work-in-progress” (2001: 2), we too suggest that Australia’s evolution in the LME category, and more specifically its industrial relations system development, and the consequences for employment relations practices of its domestic MNCs, may be a work-in-progress.

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Recent work suggests that the human ear varies significantly between different subjects and can be used for identification. In principle, therefore, using ears in addition to the face within a recognition system could improve accuracy and robustness, particularly for non-frontal views. The paper describes work that investigates this hypothesis using an approach based on the construction of a 3D morphable model of the head and ear. One issue with creating a model that includes the ear is that existing training datasets contain noise and partial occlusion. Rather than exclude these regions manually, a classifier has been developed which automates this process. When combined with a robust registration algorithm the resulting system enables full head morphable models to be constructed efficiently using less constrained datasets. The algorithm has been evaluated using registration consistency, model coverage and minimalism metrics, which together demonstrate the accuracy of the approach. To make it easier to build on this work, the source code has been made available online.

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This paper presents a novel method of audio-visual fusion for person identification where both the speech and facial modalities may be corrupted, and there is a lack of prior knowledge about the corruption. Furthermore, we assume there is a limited amount of training data for each modality (e.g., a short training speech segment and a single training facial image for each person). A new representation and a modified cosine similarity are introduced for combining and comparing bimodal features with limited training data as well as vastly differing data rates and feature sizes. Optimal feature selection and multicondition training are used to reduce the mismatch between training and testing, thereby making the system robust to unknown bimodal corruption. Experiments have been carried out on a bimodal data set created from the SPIDRE and AR databases with variable noise corruption of speech and occlusion in the face images. The new method has demonstrated improved recognition accuracy.

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This chapter describes an experimental system for the recognition of human faces from surveillance video. In surveillance applications, the system must be robust to changes in illumination, scale, pose and expression. The system must also be able to perform detection and recognition rapidly in real time. Our system detects faces using the Viola-Jones face detector, then extracts local features to build a shape-based feature vector. The feature vector is constructed from ratios of lengths and differences in tangents of angles, so as to be robust to changes in scale and rotations in-plane and out-of-plane. Consideration was given to improving the performance and accuracy of both the detection and recognition steps.

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With the rapid development of internet-of-things (IoT), face scrambling has been proposed for privacy protection during IoT-targeted image/video distribution. Consequently in these IoT applications, biometric verification needs to be carried out in the scrambled domain, presenting significant challenges in face recognition. Since face models become chaotic signals after scrambling/encryption, a typical solution is to utilize traditional data-driven face recognition algorithms. While chaotic pattern recognition is still a challenging task, in this paper we propose a new ensemble approach – Many-Kernel Random Discriminant Analysis (MK-RDA) to discover discriminative patterns from chaotic signals. We also incorporate a salience-aware strategy into the proposed ensemble method to handle chaotic facial patterns in the scrambled domain, where random selections of features are made on semantic components via salience modelling. In our experiments, the proposed MK-RDA was tested rigorously on three human face datasets: the ORL face dataset, the PIE face dataset and the PUBFIG wild face dataset. The experimental results successfully demonstrate that the proposed scheme can effectively handle chaotic signals and significantly improve the recognition accuracy, making our method a promising candidate for secure biometric verification in emerging IoT applications.

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This paper describes a study that used a mixed method approach to elicit the views of a range of stakeholders about experiences of compulsory admission to psychiatric hospital, and the use of the Mental Health Review Tribunal (MHRT). The paper begins with an introduction to the background of the study, one that took place in Northern Ireland, a region in the UK with its own mental health legislation and policy. A review of literature is then presented. This highlights some of the disadvantages that service users and carers face when dealing with professionals during and following compulsory admission to hospital. This section concludes with an overview of literature on the MHRT in the UK. A range of methods was used to gather data from the following stakeholders: five service user and carer focus group interviews (n = 44); interviews with four lawyers experienced in Tribunal work; an interview with a legal member of the Tribunal; a survey of solicitors who identified themselves as equipped to carry out Tribunal work; interviews with three managers of organisations that provided patient advocacy services; letters to hospital managers requesting information provided to patients and carers. The findings reveal a number of themes associated with these experiences of compulsory admission to hospital and subsequent use of the Tribunal. Service users and carers generally found it difficult to access relevant information about rights, information provided by hospital managers was uneven and lawyers were often not familiar with processes associated with compulsory admission. There was a range of views about the Tribunal. Most respondents felt that the Tribunal was necessary and mostly satisfactory in the way it carried out its functions, but stakeholders raised a number of issues. Carers in particular felt that they should be more involved in decision-making processes, whereas lawyers tended to be focused on more technical, legal issues. Problems of regrading prior to the Tribunal and in examining medical evidence were highlighted by lawyers. There was an appeal for better information and advice by service users and carers, and recognition of the need for better training and education for lawyers. The paper concludes with a brief discussion about current mental health law in the UK, arguing that, in this context, professionals should more proactively use information and advice that can enable service users and carers to defend their rights. Keywords: compulsory mental health; law; legal and advice services

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There are multiple reasons to expect that recognising the verbal content of emotional speech will be a difficult problem, and recognition rates reported in the literature are in fact low. Including information about prosody improves recognition rate for emotions simulated by actors, but its relevance to the freer patterns of spontaneous speech is unproven. This paper shows that recognition rate for spontaneous emotionally coloured speech can be improved by using a language model based on increased representation of emotional utterances. The models are derived by adapting an already existing corpus, the British National Corpus (BNC). An emotional lexicon is used to identify emotionally coloured words, and sentences containing these words are recombined with the BNC to form a corpus with a raised proportion of emotional material. Using a language model based on that technique improves recognition rate by about 20%. (c) 2005 Elsevier Ltd. All rights reserved.

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The objective of this multicentre study was to undertake a systematic comparison of face-to-face consultations and teleconsultations performed using low-cost videoconferencing equipment. One hundred and twenty-six patients were enrolled by their general practitioners across three sites. Each patient underwent a teleconsultation with a distant dermatologist followed by a traditional face-to-face consultation with a dermatologist. The main outcome measures were diagnostic concordance rates, management plans and patient and doctor satisfaction. One hundred and fifty-five diagnoses were identified by the face-to-face consultations from the sample of 126 patients. Identical diagnoses were recorded from both types of consultation in 59% of cases. Teledermatology consultations missed a secondary diagnosis in 6% of cases and were unable to make a useful diagnosis in 11% of cases. Wrong diagnoses were made by the teledermatologist in 4% of cases. Dermatologists were able to make a definitive diagnosis by face-to-face consultations in significantly more cases than by teleconsultations (P = 0.001). Where both types of consultation resulted in a single diagnosis there was a high level of agreement (kappa = 0.96, lower 95% confidence limit 0.91-1.00). Overall follow-up rates from both types of consultation were almost identical. Fifty per cent of patients seen could have been managed using a single videoconferenced teleconsultation without any requirement for further specialist intervention. Patients reported high levels of satisfaction with the teleconsultations. General practitioners reported that 75% of the teleconsultations were of educational benefit. This study illustrates the potential of telemedicine to diagnose and manage dermatology cases referred from primary care. Once the problem of image quality has been addressed, further studies will be required to investigate the cost-effectiveness of a teledermatology service and the potential consequences for the provision of dermatological services in the U.K.