1,720,963 research outputs found
Multi-modal Active Authentication of Smartphone Users
Get PDFWith the increasing usage of smartphones not only as communication devices but also as the port of entry for a wide variety of user accounts at different information sensitivity levels, the need for hassle-free authentication is on the rise. Going beyond the traditional one-time authentication concept, active authentication (AA) schemes are emerging which authenticates users periodically in the background without the need for any user interaction. The purpose of this research is to explore different aspects of the AA problem and develop viable solutions by extracting unique biometric traits of the user from the wide variety of usage data obtained from Smartphone sensors. The key aspects of our research are the development of different components of user verification algorithms based on (a) face images from the front camera and (b) data from modalities other than the face.
Since generic face detection algorithms do not perform very well in the mobile domain due to a significant presence of occluded and partially visible faces, we propose facial segment-based face detection technique to handle the challenge of partial faces in the mobile domain. We have developed three increasingly accurate proposal-based face detection methods, namely Facial Segment-based Face Detector (FSFD), SegFace and DeepSegFace, respectively, which perform binary classification on the results of a novel proposal generator that utilizes facial segments to obtain face-proposals. We also propose the Deep Regression-based User Image Detector (DRUID) network which shifts from the classification to the regression paradigm to avoid the need for proposal generation and thereby, achieves better processing speed and accuracy. DeepSegFace and DRUID have unique network architectures with customized loss functions and utilize a novel data augmentation scheme to train on a relatively small amount of data. The proposed methods, especially DRUID show superior performance over other state-of-the-art face detectors in terms of precision-recall and ROC curve on two mobile face datasets.
We extended the concept of facial-segments to facial attribute detection for partially visible faces, a topic rarely addressed in the literature. We developed a deep convolutional neural network-based method named Segment-wise, Partial, Localized Inference in Training Facial Attribute Classification Ensembles (SPLITFACE) to detect attributes reliably from partially occluded faces. Taking several facial segments and the full face as input, SPLITFACE takes a data-driven approach to determine which attributes are localized in which facial segments. The unique architecture of the network allows each attribute to be predicted by multiple segments, which permits the implementation of committee machine techniques for combining local and global decisions to boost performance. Our evaluations on the full CelebA and LFWA datasets and their modified partial-visibility versions show that SPLITFACE significantly outperforms other recent attribute detection methods, especially for partial faces and for cross-domain experiments.
We also explored the potentials of two less popular modalities namely, location history and application-usage, for active authentication. Aiming to discover the pattern of life of a user, we processed the location traces into separate state space models for each user and developed the Marginally Smoothed Hidden Markov Model (MSHMM) algorithm to authenticate the current user based on the most recent sequence of observations. The method takes into consideration the sparsity of the available data, the transition phases between states, the timing information and also the unforeseen states. We looked deeper into the impact of unforeseen and unknown states in another research work where we evaluated the feasibility of application usage behavior of the users as a potential solution to the active authentication problem. Our experiments show that it is essential to take unforeseen states into account when designing an authentication system with sparse data and marginal-smoothing techniques are very useful in this regard.
We conclude this dissertation with the description of some ongoing efforts and future directions of research related the topics discussed in addition to a summary of all the contributions and impacts of this research work
The (Computer) Vision of Sports:Recent Trends in Research and Commercial Systems for Sport Analytics
No full textSport and technology are in many ways closely connected. Athletes seek new ways to push their performance, coaches try to gain advantage from all available data, and broadcasters aim to provide a unique and enhanced experience for the viewers.The advancements in computer vision technology have had a huge impact on sports analysis and visualisation in recent years. In this chapter, we first provide an overview of how computer vision technology is currently used in commercial applications of sports. This includes game and performance analysis by both individual athletes and professional clubs, technology for assisting officiating in games, and techniques for creating individualised visual content and enhancing broadcasting.Secondly, we discuss the current trends in research of computer vision for sports analysis. We have identified two main lines of research to cover in detail: methods aimed at (ball-based) team sports, and methods aimed at analysis of individual athletes. Finally, we discuss how we believe recent computer vision methods can continue changing the sports domain in the future
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Exploiting Wavelet and Prosody-related Features for the Detection of Voice Disorders
Get PDFAn approach for the detection of voice disorders exploiting wavelet and prosody-related properties of speech is presented in this paper. Based on the normalized energy contents of the Discrete Wavelet Transform (DWT) coefficients over all voice frames, several statistical measures are first determined. Then, the idea of some prosody-related voice properties, such as mean pitch, jitter and shimmer are utilized to compute similar statistical measures over all the frames. A set of statistical measures of the normalized energy contents of the DWT coefficients is combined with a set of statistical measures of the extracted prosody-related voice properties in order to form a feature vector to be used in both training and testing phases. Two categories of voice samples namely, healthy and disordered are considered here thus formulating the problem in the proposed method as a two-class problem to be solved. Finally, an Euclidean Distance based classifier is used to handle the feature vector for the purpose of detecting the disordered voice. A number of simulations is carried out and it is shown that the statistical analysis based on wavelet and prosody-related properties can effectively detect a variety of voice disorders from the mixture of healthy and disordered voices
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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