234 research outputs found

    Assessing the Influencing Factors on the Accuracy of Underage Facial Age Estimation

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    Swift response to the detection of endangered minors is an ongoing concern for law enforcement. Many child-focused investigations hinge on digital evidence discovery and analysis. Automated age estimation techniques are needed to aid in these investigations to expedite this evidence discovery process, and decrease investigator exposure to traumatic material. Automated techniques also show promise in decreasing the overflowing backlog of evidence obtained from increasing numbers of devices and online services. A lack of sufficient training data combined with natural human variance has been long hindering accurate automated age estimation -- especially for underage subjects. This paper presented a comprehensive evaluation of the performance of two cloud age estimation services (Amazon Web Service's Rekognition service and Microsoft Azure's Face API) against a dataset of over 21,800 underage subjects. The objective of this work is to evaluate the influence that certain human biometric factors, facial expressions, and image quality (i.e. blur, noise, exposure and resolution) have on the outcome of automated age estimation services. A thorough evaluation allows us to identify the most influential factors to be overcome in future age estimation systems

    Multimodal Fusion of Polynomial Classifiers for Automatic Person Recognition

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    With the prevalence of the information age, privacy and personalization are forefront in today\u27s society. As such, biometrics are viewed as essential components of current and evolving technological systems. Consumers demand unobtrusive and noninvasive approaches. In our previous work, we have demonstrated a speaker verification system that meets these criteria. However, there are additional constraints for fielded systems. The required recognition transactions are often performed in adverse environments and across diverse populations, necessitating robust solutions. There are two significant problem areas in current generation speaker verification systems. The first is the difficulty in acquiring clean audio signals (in all environments) without encumbering the user with a head-mounted close-talking microphone. Second, unimodal biometric systems do not work with a significant percentage of the population. To combat these issues, multimodal techniques are being investigated to improve system robustness to environmental conditions, as well as improve overall accuracy across the population. We propose a multimodal approach that builds on our current state-of-the-art speaker verification technology. In order to maintain the transparent nature of the speech interface, we focus on optical sensing technology to provide the additional modality–giving us an audio-visual person recognition system. For the audio domain, we use our existing speaker verification system. For the visual domain, we focus on lip motion. This is chosen, rather than static face or iris recognition, because it provides dynamic information about the individual. In addition, the lip dynamics can aid speech recognition to provide liveness testing. The visual processing method makes use of both color and edge information, combined within a Markov random field (MRF) framework, to localize the lips. Geometric features are extracted and input to a polynomial classifier for the person recognition process. A late integration approach, based on a probabilistic model, is employed to combine the two modalities. The system is tested on the XM2VTS database combined with AWGN (in the audio domain) over a range of signal-to-noise ratios

    GPU-accelerated lip-tracking library

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    A major part of having correct pronunciation when learning a new language is moving your lips in the correct way. This is a difficult thing to learn and to teach. One solution to this is software which tracks a student\u27s lip movements and provides feedback. This paper describes how we have created a C++ library to accurately track lips in provided images. Further, this library attempts to use a CUDA-enabled GPU implementation to improve the algorithm\u27s performance. It will fall back on a CPU implementation if such a GPU is not found. As a result, the lip tracking library runs on Windows, Linux, and OS X, as well as Android devices

    How parfums Christian Dior could address its existing make-up range Dior backstage to men?: how to sell make-up to men?

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    This Master’s thesis has been developed under the form of an in-company project as a marketing and communication plan for the French company Parfums Christian Dior. The company has international influence and is one of the leader on the luxury cosmetic market and possesses a growing range addressed to millennials and not strongly gendered yet, thus letting the space to change a bit its positioning for reaching men. In order to build this new positioning, we will study the impact of the digital on consumer behavior regarding cosmetics purchase and on the customer decision-making process, the key roles implied in a purchase and the evolution of the meaning of “Man” in our occidental society. Furthermore, it was necessary to collect data from the industry, the market, the competitors and about consumer behavior toward cosmetics and especially. This data collection has enabled us to better understand how and where to reach men, where competitors did not go or did not know how to address their strategy. An internal analysis has also been conducted to make a state of play of Dior’s strengths and weaknesses, based on its range, image, positioning and distribution strategy. The focus of this thesis is to understand how Dior could use its strengths and weaknesses to take the opportunities of the market and to counter the threats for reaching and selling its make-up to men, a very specific and hard to reach target.Esta tese de mestrado foi desenvolvida na forma de um projeto de comunicação e marketing in-company para a empresa francesa Parfums Christian Dior. A empresa possui presença internacional e estĂĄ entre os lĂ­deres no mercado de cosmĂ©ticos de luxo e possui uma gama crescente voltada para a geração do milĂȘnio e ainda nĂŁo fortemente de gĂȘnero, deixando assim o espaço para mudar um pouco seu posicionamento para alcançar os homens. Visando construir este novo posicionamento e o plano de comunicação associado foi criado um framework agregando os principais conceitos. Estudaremos o impacto do digital no hĂĄbito de consumo de cosmĂ©ticos e o processo de decisĂŁo do consumidor, os principais papeis implicados na compra e a evolução do significado de “Homem” na nossa sociedade ocidental. Ainda mais, foi necessĂĄrio coletar informaçÔes da indĂșstria, do mercado, de competidores e o hĂĄbito de consumo de cosmĂ©ticos, especialmente em homens. Esta coleta de informaçÔes nos possibilitou melhor compreender como e onde alcançar os homens, onde competidores nĂŁo foram ou nĂŁo souberam como aplicar suas estratĂ©gias. Uma anĂĄlise interna tambĂ©m foi feita para averiguar a situação que se encontram as forças e fraquezas da Dior, baseado no seu escopo, imagem, posicionamento e distribuição estratĂ©gica. O foco desta tese Ă© compreender como Dior poderia utilizar suas forças e fraquezas em oportunidades mercadolĂłgicas e preparar-se para possĂ­veis adversidades com a proposta de venda de maquiagem masculina, um objetivo deveras difĂ­cil e especĂ­fico

    Continuous Audio-Visual Speech Recognition

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    We address the problem of robust lip tracking, visual speech feature extraction, and sensor integration for audio-visual speech recognition applications. An appearance based model of the articulators, which represents linguistically important features, is learned from example images and is used to locate, track, and recover visual speech information. We tackle the problem of joint temporal modelling of the acoustic and visual speech signals by applying Multi-Stream hidden Markov models. This approach allows the use of different temporal topologies and levels of stream integration and hence enables to model temporal dependencies more accurately. The system has been evaluated for a continuously spoken digit recognition task of 37 subjects

    Improved facial feature fitting for model based coding and animation

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    EThOS - Electronic Theses Online ServiceGBUnited Kingdo

    The effects of destination image and perceived risk on revisit intention: a study in the south eastern coast of Sabah, Malaysia

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    This study investigated the effects of destination image and perceived risk on revisit intention in the South Eastern Coast of Sabah, Malaysia. A total of 171 questionnaires were collected from international tourists through a self-administered questionnaire. The result of this study identified that three dimensions of destination image (travel environment, natural attraction, entertainment, and events) had significant effects on revisit intention. However, perceived risk was not important to the tourists’ revisit intention. The findings have implications on the tourism industry, especially for key players such as the tourism board and travel companies. It also serves as a reference to destinations with a similar risk background

    FEATURE-BASED FACE DETECTION: A SURVEY

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    Human and computer vision has a vital role in intelligent interaction with computer, face recognition is one of the subjects that have a wide area in researches, a big effort has been exerted in last decades for face recognition, face detection, face tracking, as yet new algorithms for building fully automated system are required, these algorithms should be robust and efficient. The first step of any face recognition system is face detection, the goal of face detection is the extraction of face region within image, taking into consideration lightning, orientation and pose variation, whenever this step accurate the result of face recognition will be better, this paper introduce a survey of techniques and methods of feature based face detection

    Automatic extraction of geometric lip features with application to multi-modal speaker identification

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    In this paper we consider the problem of automatic extraction of the geometric lip features for the purposes of multi-modal speaker identification. The use of visual information from the mouth region can be of great importance for improving the speaker identification system performance in noisy conditions. We propose a novel method for automated lip features extraction that utilizes color space transformation and a fuzzy-based c-means clustering technique. Using the obtained visual cues closed-set audio-visual speaker identification experiments are performed on the CUAVE database, [1] showing promising results
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