14 resultados para Face representation and recognition

em Digital Commons at Florida International University


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This dissertation establishes a novel system for human face learning and recognition based on incremental multilinear Principal Component Analysis (PCA). Most of the existing face recognition systems need training data during the learning process. The system as proposed in this dissertation utilizes an unsupervised or weakly supervised learning approach, in which the learning phase requires a minimal amount of training data. It also overcomes the inability of traditional systems to adapt to the testing phase as the decision process for the newly acquired images continues to rely on that same old training data set. Consequently when a new training set is to be used, the traditional approach will require that the entire eigensystem will have to be generated again. However, as a means to speed up this computational process, the proposed method uses the eigensystem generated from the old training set together with the new images to generate more effectively the new eigensystem in a so-called incremental learning process. In the empirical evaluation phase, there are two key factors that are essential in evaluating the performance of the proposed method: (1) recognition accuracy and (2) computational complexity. In order to establish the most suitable algorithm for this research, a comparative analysis of the best performing methods has been carried out first. The results of the comparative analysis advocated for the initial utilization of the multilinear PCA in our research. As for the consideration of the issue of computational complexity for the subspace update procedure, a novel incremental algorithm, which combines the traditional sequential Karhunen-Loeve (SKL) algorithm with the newly developed incremental modified fast PCA algorithm, was established. In order to utilize the multilinear PCA in the incremental process, a new unfolding method was developed to affix the newly added data at the end of the previous data. The results of the incremental process based on these two methods were obtained to bear out these new theoretical improvements. Some object tracking results using video images are also provided as another challenging task to prove the soundness of this incremental multilinear learning method.

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This dissertation develops an innovative approach towards less-constrained iris biometrics. Two major contributions are made in this research endeavor: (1) Designed an award-winning segmentation algorithm in the less-constrained environment where image acquisition is made of subjects on the move and taken under visible lighting conditions, and (2) Developed a pioneering iris biometrics method coupling segmentation and recognition of the iris based on video of moving persons under different acquisitions scenarios. The first part of the dissertation introduces a robust and fast segmentation approach using still images contained in the UBIRIS (version 2) noisy iris database. The results show accuracy estimated at 98% when using 500 randomly selected images from the UBIRIS.v2 partial database, and estimated at 97% in a Noisy Iris Challenge Evaluation (NICE.I) in an international competition that involved 97 participants worldwide involving 35 countries, ranking this research group in sixth position. This accuracy is achieved with a processing speed nearing real time. The second part of this dissertation presents an innovative segmentation and recognition approach using video-based iris images. Following the segmentation stage which delineates the iris region through a novel segmentation strategy, some pioneering experiments on the recognition stage of the less-constrained video iris biometrics have been accomplished. In the video-based and less-constrained iris recognition, the test or subject iris videos/images and the enrolled iris images are acquired with different acquisition systems. In the matching step, the verification/identification result was accomplished by comparing the similarity distance of encoded signature from test images with each of the signature dataset from the enrolled iris images. With the improvements gained, the results proved to be highly accurate under the unconstrained environment which is more challenging. This has led to a false acceptance rate (FAR) of 0% and a false rejection rate (FRR) of 17.64% for 85 tested users with 305 test images from the video, which shows great promise and high practical implications for iris biometrics research and system design.

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Perception and recognition of faces are fundamental cognitive abilities that form a basis for our social interactions. Research has investigated face perception using a variety of methodologies across the lifespan. Habituation, novelty preference, and visual paired comparison paradigms are typically used to investigate face perception in young infants. Storybook recognition tasks and eyewitness lineup paradigms are generally used to investigate face perception in young children. These methodologies have introduced systematic differences including the use of linguistic information for children but not infants, greater memory load for children than infants, and longer exposure times to faces for infants than for older children, making comparisons across age difficult. Thus, research investigating infant and child perception of faces using common methods, measures, and stimuli is needed to better understand how face perception develops. According to predictions of the Intersensory Redundancy Hypothesis (IRH; Bahrick & Lickliter, 2000, 2002), in early development, perception of faces is enhanced in unimodal visual (i.e., silent dynamic face) rather than bimodal audiovisual (i.e., dynamic face with synchronous speech) stimulation. The current study investigated the development of face recognition across children of three ages: 5 – 6 months, 18 – 24 months, and 3.5 – 4 years, using the novelty preference paradigm and the same stimuli for all age groups. It also assessed the role of modality (unimodal visual versus bimodal audiovisual) and memory load (low versus high) on face recognition. It was hypothesized that face recognition would improve across age and would be enhanced in unimodal visual stimulation with a low memory load. Results demonstrated a developmental trend (F(2, 90) = 5.00, p = 0.009) with older children showing significantly better recognition of faces than younger children. In contrast to predictions, no differences were found as a function of modality of presentation (bimodal audiovisual versus unimodal visual) or memory load (low versus high). This study was the first to demonstrate a developmental improvement in face recognition from infancy through childhood using common methods, measures and stimuli consistent across age.

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This study examined the effect of schemas on consistency and accuracy of memory across interviews, providing theoretical hypotheses explaining why inconsistencies may occur. The design manipulated schema-typicality of items (schema-typical and atypical), question format (free-recall, cued-recall and recognition) and retention interval (immediate/2 week and 2 week/4 week). Consistency, accuracy and experiential quality of memory were measured. ^ All independent variables affected accuracy and experiential quality of memory while question format was the only variable affecting consistency. These results challenge the commonly held notion in the legal arena that consistency is a proxy for accuracy. The study also demonstrates that other variables, such as item-typicality and retention interval have different effects on consistency and accuracy in memory. ^

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This longitudinal study provides a detailed description of the transition in the Bahamas from British colony to independent country. It analyzes the ongoing process of legitimation and delegitimation of Bahamian political parties and of the transfer of authority from the white minority to the black majority. It is a story of social and political struggles that take place within the quarter century following World War II. These struggles are analyzed within a theoretical framework which focuses on the meaning of symbols used to support claims to authority, and/or which function to delegitimize alternative claims. Specifically, this study looks at the delegitimization of the institutions of colonialism and the concurrent profession of symbols to support both independence and a fully enfranchised democracy in the Bahamas. ^ The research methodology includes an extensive analysis of official British colonial documents, private governmental dispatches, and contemporaneous newspaper articles. The sources were primarily the Public Records Office of Great Britain; the Archives of the Bahamas; and the Institute for Social and Economic Research, University of the West Indies. Secondary literature on civil rights, political science, religion, Black Nationalism, corruption, social theory, and popular culture was studied. Two hundred days of participant observation, spread over seven years of study, resulted in notes from which information was gleaned. During that time, seventeen open-ended interviews with a cross section of Bahamians (male and female, black and white) who lived through this period were recorded, information from which was also incorporated. ^ A detailed description of the socio-historical process, and an analysis of data, demonstrates how the black majority's desire for political representation, and future independence, pressured Great Britain to come into line with the desires of the majority of Bahamians. The symbolic universe that had historically divided white from black now urged dramatic social and political change. ^ The documents and testimonials studied demonstrate how symbols and symbolic events supported and/or undercut the claims to legitimacy proffered by different groups in the Bahamas in their respective attempts to solidify their social and political position within the society. ^

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With the proliferation of multimedia data and ever-growing requests for multimedia applications, there is an increasing need for efficient and effective indexing, storage and retrieval of multimedia data, such as graphics, images, animation, video, audio and text. Due to the special characteristics of the multimedia data, the Multimedia Database management Systems (MMDBMSs) have emerged and attracted great research attention in recent years. Though much research effort has been devoted to this area, it is still far from maturity and there exist many open issues. In this dissertation, with the focus of addressing three of the essential challenges in developing the MMDBMS, namely, semantic gap, perception subjectivity and data organization, a systematic and integrated framework is proposed with video database and image database serving as the testbed. In particular, the framework addresses these challenges separately yet coherently from three main aspects of a MMDBMS: multimedia data representation, indexing and retrieval. In terms of multimedia data representation, the key to address the semantic gap issue is to intelligently and automatically model the mid-level representation and/or semi-semantic descriptors besides the extraction of the low-level media features. The data organization challenge is mainly addressed by the aspect of media indexing where various levels of indexing are required to support the diverse query requirements. In particular, the focus of this study is to facilitate the high-level video indexing by proposing a multimodal event mining framework associated with temporal knowledge discovery approaches. With respect to the perception subjectivity issue, advanced techniques are proposed to support users' interaction and to effectively model users' perception from the feedback at both the image-level and object-level.

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In the past two decades, multi-agent systems (MAS) have emerged as a new paradigm for conceptualizing large and complex distributed software systems. A multi-agent system view provides a natural abstraction for both the structure and the behavior of modern-day software systems. Although there were many conceptual frameworks for using multi-agent systems, there was no well established and widely accepted method for modeling multi-agent systems. This dissertation research addressed the representation and analysis of multi-agent systems based on model-oriented formal methods. The objective was to provide a systematic approach for studying MAS at an early stage of system development to ensure the quality of design. ^ Given that there was no well-defined formal model directly supporting agent-oriented modeling, this study was centered on three main topics: (1) adapting a well-known formal model, predicate transition nets (PrT nets), to support MAS modeling; (2) formulating a modeling methodology to ease the construction of formal MAS models; and (3) developing a technique to support machine analysis of formal MAS models using model checking technology. PrT nets were extended to include the notions of dynamic structure, agent communication and coordination to support agent-oriented modeling. An aspect-oriented technique was developed to address the modularity of agent models and compositionality of incremental analysis. A set of translation rules were defined to systematically translate formal MAS models to concrete models that can be verified through the model checker SPIN (Simple Promela Interpreter). ^ This dissertation presents the framework developed for modeling and analyzing MAS, including a well-defined process model based on nested PrT nets, and a comprehensive methodology to guide the construction and analysis of formal MAS models.^

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Over the last decade, the Colombian military has successfully rolled back insurgent groups, cleared and secured conflict zones, and enabled the extraction of oil and other key commodity exports. As a result, official policies of both the Uribe and Santos governments have promoted the armed forces to participate to an unprecedented extent in economic activities intended to consolidate the gains of the 2000s. These include formal involvement in the economy, streamlined in a consortium of military enterprises and social foundations that are intended to put the Colombian defense sector “on the map” nationally and internationally, and informal involvement expanded mainly through new civic action development projects intended to consolidate the security gains of the 2000s. However, failure to roll back paramilitary groups other than through the voluntary amnesty program of 2005 has facilitated the persistence of illicit collusion by military forces with reconstituted “neoparamilitary” drug trafficking groups. It is therefore crucially important to enhance oversight mechanisms and create substantial penalties for collusion with illegal armed groups. This is particularly important if Colombia intends to continue its new practice of exporting its security model to other countries in the region. The Santos government has initiated several promising reforms to enhance state capacity, institutional transparence, and accountability of public officials to the rule of law, which are crucial to locking in security gains and revitalizing democratic politics. Efforts to diminish opportunities for illicit association between the armed forces and criminal groups should complement that agenda, including the following: Champion breaking existing ties between the military and paramilitary successor groups through creative policies involving a mixture of punishments and rewards directed at the military; Investigation and extradition proceedings of drug traffickers, probe all possible ties, including as a matter of course the possibility of Colombian military collaboration. Doing so rigorously may have an important effect deterring military collusion with criminal groups. Establish and enforce zero-tolerance policies at all military ranks regarding collusion with criminal groups; Reward military units that are effective and also avoid corruption and criminal ties by providing them with enhanced resources and recognition; Rely on the military for civic action and development assistance as minimally as possible in order to build long-term civilian public sector capacity and to reduce opportunities for routine exposure of military forces to criminal groups circulating in local populations.

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Over the past five years, XML has been embraced by both the research and industrial community due to its promising prospects as a new data representation and exchange format on the Internet. The widespread popularity of XML creates an increasing need to store XML data in persistent storage systems and to enable sophisticated XML queries over the data. The currently available approaches to addressing the XML storage and retrieval issue have the limitations of either being not mature enough (e.g. native approaches) or causing inflexibility, a lot of fragmentation and excessive join operations (e.g. non-native approaches such as the relational database approach). ^ In this dissertation, I studied the issue of storing and retrieving XML data using the Semantic Binary Object-Oriented Database System (Sem-ODB) to leverage the advanced Sem-ODB technology with the emerging XML data model. First, a meta-schema based approach was implemented to address the data model mismatch issue that is inherent in the non-native approaches. The meta-schema based approach captures the meta-data of both Document Type Definitions (DTDs) and Sem-ODB Semantic Schemas, thus enables a dynamic and flexible mapping scheme. Second, a formal framework was presented to ensure precise and concise mappings. In this framework, both schemas and the conversions between them are formally defined and described. Third, after major features of an XML query language, XQuery, were analyzed, a high-level XQuery to Semantic SQL (Sem-SQL) query translation scheme was described. This translation scheme takes advantage of the navigation-oriented query paradigm of the Sem-SQL, thus avoids the excessive join problem of relational approaches. Finally, the modeling capability of the Semantic Binary Object-Oriented Data Model (Sem-ODM) was explored from the perspective of conceptually modeling an XML Schema using a Semantic Schema. ^ It was revealed that the advanced features of the Sem-ODB, such as multi-valued attributes, surrogates, the navigation-oriented query paradigm, among others, are indeed beneficial in coping with the XML storage and retrieval issue using a non-XML approach. Furthermore, extensions to the Sem-ODB to make it work more effectively with XML data were also proposed. ^

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Why and under what conditions have the Kurds become agents of change in the Middle East in terms of democratization? Why did the Kurds' role as democratic agents become particularly visible in the 1990s? How does the Kurdish movement's turn to democratic discourse affect the political systems of Turkey, Iran, Iraq and Syria? What are the implications of the Kurds' adoption of "democratic discourse" for the transnational aspect of the Kurdish movement? Since the early 1990s, Kurdish national movements in Turkey, Iran, Iraq and Syria have undergone important political and ideological transformations. As a result of the Kurds' growing role in shaping the debates on human rights and democratization in these four countries, the Kurdish national movement has acquired a dual character: an ethno-cultural struggle for the recognition of Kurdish identity, and a democratization movement that seeks to redefine the concepts of governance and citizenship in Turkey, Iran, Iraq and Syria. The process transformation has affected relations between the Kurdish movements and their respective central governments in significant ways. On the basis of face-to-face interviews and archival research conducted in Turkey, Iraq and parts of Europe, the present work challenges the current narrative of Kurdish nationalism, which is predominantly drawn from a statist interpretation of Kurdish nationalist goals, and argues instead that the Kurdish question is no longer a problem of statelessness but a problem of democracy in Turkey, Iran, Iraq and Syria. The main contributions of this work are three fold. First, the research unfolds the reasons behind the growing emphasis of the Kurdish movement on the concepts of democracy, human rights, and political participation, which started in the early 1990s. Second, the findings challenge the existing scholarship that explains Kurdish nationalism as a problem of statelessness and shifts the focus to the transformative potentials of the Kurdish national movement in Turkey, Iran, Iraq and Syria through a comparative lens. Third, this work explores the complex transnational coordination and negotiations between the Kurdish movements across borders and explains the regional repercussions of this process.

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The purpose of this thesis was to investigate Nico Assumpção. He has not received the interest and recognition of the American jazz audience, despite having recorded and performed with some of the greatest jazz musicians in the world. Four works were transcribed and analyzed in detail with respect to the following issues and elements: rhythmic conception, bass techniques and melodic and harmonic characteristics. Observations were made and trends examined in his music as well as his improvisational style, which illustrates his stylistic significance. Results show that Nico Assumpção is indeed representative of the Jazz Fusion and Latin Jazz styles, despite his low profile in jazz literature. This is seen in his electric bass playing through his use of Brazilian and other Latin elements in conjunction with a jazz vocabulary. This is exemplified through the transcriptions and analysis of his works.

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Background: Mothers with HIV often face personal and environmental risks for poor maternal health behaviors and infant neglect, even when HIV transmission to the infant was prevented. Maternal-fetal attachment (MFA), the pre-birth relationship of a woman with her fetus, may be the precursor to maternal caregiving. Using the strengths perspective in social work, which embeds MFA within a socio-ecological conceptual framework, it is hypothesized that high levels of maternal-fetal attachment may protect mothers and infants against poor maternal health behaviors. Objective: To assess whether MFA together with history of substance use, living marital status, planned pregnancy status, and timing of HIV diagnosis predict three desirable maternal health behaviors (pregnancy care, adherence to prenatal antiretroviral therapy–ART, and infant’s screening clinic care) among pregnant women with HIV/AIDS. Method: Prospective observation and hypothesis-testing multivariate analyses. Over 17 consecutive months, all eligible English- or Spanish-speaking pregnant women with HIV ( n = 110) were approached in the principal obstetric and screening clinics in Miami-Dade County, Florida at 24 weeks’ gestation; 82 agreed to enroll. During three data collection periods from enrollment until 16 weeks after childbirth (range: 16 to 32 weeks), participants reported on socio-demographic and predictor variables, MFA, and pregnancy care. Measures of adherence to ART and infant care were extracted from medical records. Findings: Sociodemographic, pregnancy, and HIV disease characteristics in this sample suggest changes in the makeup of HIV-infected pregnant women parallel to the evolution of the HIV epidemic in the USA over the past two decades. The MFA model predicted maternal health behaviors for pregnancy care (R2 = .37), with MFA, marital living status, and planned pregnancy status independently contributing ( = .50, = .28, = .23, respectively). It did not predict adherence to ART medication or infant care. Relevance: These findings provide the first focused evidence of the protective role of MFA against poor maternal health behaviors among pregnant women with HIV, in the presence of adverse life circumstances. Social desirability biases in some self-report measures may limit the findings. Suggestions are made for orienting future inquiry on maternal health behaviors during childbirth toward relationship and protection.

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Several researchers have investigated the effects of alcohol on memory. Few researchers have studied the effects of alcohol on an eyewitness's recall and recognition of crime events. This study proposed to examine the effects of alcohol and viewing conditions on subjects' ability to recall information regarding a videotaped bank robbery. Thirty male and 22 female subjects participated in a 2 (consumption: alcohol v. no alcohol) x 2 (lighting: good v. poor) factorial experiment with Average Accuracy and Total Amount of Information recalled as the primary dependent measures. There was no significant difference between the Intoxicated and Sober subjects regarding the amount of information recalled or their average accuracy. The main effect for lighting conditions and gender differences were also not significant.

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Thanks to the advanced technologies and social networks that allow the data to be widely shared among the Internet, there is an explosion of pervasive multimedia data, generating high demands of multimedia services and applications in various areas for people to easily access and manage multimedia data. Towards such demands, multimedia big data analysis has become an emerging hot topic in both industry and academia, which ranges from basic infrastructure, management, search, and mining to security, privacy, and applications. Within the scope of this dissertation, a multimedia big data analysis framework is proposed for semantic information management and retrieval with a focus on rare event detection in videos. The proposed framework is able to explore hidden semantic feature groups in multimedia data and incorporate temporal semantics, especially for video event detection. First, a hierarchical semantic data representation is presented to alleviate the semantic gap issue, and the Hidden Coherent Feature Group (HCFG) analysis method is proposed to capture the correlation between features and separate the original feature set into semantic groups, seamlessly integrating multimedia data in multiple modalities. Next, an Importance Factor based Temporal Multiple Correspondence Analysis (i.e., IF-TMCA) approach is presented for effective event detection. Specifically, the HCFG algorithm is integrated with the Hierarchical Information Gain Analysis (HIGA) method to generate the Importance Factor (IF) for producing the initial detection results. Then, the TMCA algorithm is proposed to efficiently incorporate temporal semantics for re-ranking and improving the final performance. At last, a sampling-based ensemble learning mechanism is applied to further accommodate the imbalanced datasets. In addition to the multimedia semantic representation and class imbalance problems, lack of organization is another critical issue for multimedia big data analysis. In this framework, an affinity propagation-based summarization method is also proposed to transform the unorganized data into a better structure with clean and well-organized information. The whole framework has been thoroughly evaluated across multiple domains, such as soccer goal event detection and disaster information management.