850 resultados para Visual Performance
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The degree to which a person relies on visual stimuli for spatial orientation is termed visual dependency (VD). VD is considered a perceptual trait or cognitive style influenced by psychological factors and mediated by central re-weighting of the sensory inputs involved in spatial orientation. VD is often measured using the rod-and-disk test, wherein participants align a central rod to the subjective visual vertical (SVV) in the presence of a background that is either stationary or rotating around the line of sight - dynamic SVV. Although this task has been employed to assess VD in health and vestibular disease, it is unknown what effect torsional nystagmic eye movements may have on individual performance. Using caloric ear irrigation, 3D video-oculography and the rod-and-disk test, we show that caloric torsional nystagmus modulates measures of visual dependency and demonstrate that increases in tilt after irrigation are positively correlated with changes in ocular torsional eye movements. When the direction of the slow phase of the torsional eye movement induced by the caloric is congruent with that induced by the rotating visual stimulus, there is a significant increase in tilt. When these two torsional components are in opposition there is a decrease. These findings show that measures of visual dependence can be influenced by oculomotor responses induced by caloric stimulation. The findings are of significance for clinical studies as they indicate that VD, which often increases in vestibular disorders, is not only modulated by changes in cognitive style but also by eye movements, in particular nystagmus.
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With the world of professional sports shifting towards employing better sport analytics, the demand for vision-based performance analysis is growing increasingly in recent years. In addition, the nature of many sports does not allow the use of any kind of sensors or other wearable markers attached to players for monitoring their performances during competitions. This provides a potential application of systematic observations such as tracking information of the players to help coaches to develop their visual skills and perceptual awareness needed to make decisions about team strategy or training plans. My PhD project is part of a bigger ongoing project between sport scientists and computer scientists involving also industry partners and sports organisations. The overall idea is to investigate the contribution technology can make to the analysis of sports performance on the example of team sports such as rugby, football or hockey. A particular focus is on vision-based tracking, so that information about the location and dynamics of the players can be gained without any additional sensors on the players. To start with, prior approaches on visual tracking are extensively reviewed and analysed. In this thesis, methods to deal with the difficulties in visual tracking to handle the target appearance changes caused by intrinsic (e.g. pose variation) and extrinsic factors, such as occlusion, are proposed. This analysis highlights the importance of the proposed visual tracking algorithms, which reflect these challenges and suggest robust and accurate frameworks to estimate the target state in a complex tracking scenario such as a sports scene, thereby facilitating the tracking process. Next, a framework for continuously tracking multiple targets is proposed. Compared to single target tracking, multi-target tracking such as tracking the players on a sports field, poses additional difficulties, namely data association, which needs to be addressed. Here, the aim is to locate all targets of interest, inferring their trajectories and deciding which observation corresponds to which target trajectory is. In this thesis, an efficient framework is proposed to handle this particular problem, especially in sport scenes, where the players of the same team tend to look similar and exhibit complex interactions and unpredictable movements resulting in matching ambiguity between the players. The presented approach is also evaluated on different sports datasets and shows promising results. Finally, information from the proposed tracking system is utilised as the basic input for further higher level performance analysis such as tactics and team formations, which can help coaches to design a better training plan. Due to the continuous nature of many team sports (e.g. soccer, hockey), it is not straightforward to infer the high-level team behaviours, such as players’ interaction. The proposed framework relies on two distinct levels of performance analysis: low-level performance analysis, such as identifying players positions on the play field, as well as a high-level analysis, where the aim is to estimate the density of player locations or detecting their possible interaction group. The related experiments show the proposed approach can effectively explore this high-level information, which has many potential applications.
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Se desarrolló un estudio descriptivo con el objetivo de evaluar el rendimiento escolar así como tipos de errores en la lectura en niños con alteraciones de la función visual. En el estudio participaron 672 niños del Municipio de Lisboa (7.69±1.19 años): grupo de control (función visual normal=562) y grupo experimental (alteraciones da función visual=110). Se cuestionaron 34 profesores acerca del rendimiento escolar y lectura a través de un cuestionario validado. Para la evaluación en la lectura se empleó la prueba de lectura de 34 palabras sueltas. Los niños con la función visual alterada mostraron niveles más bajos de rendimiento escolar. Estaban en el nivel "negativo" del 10,9% de los niños con la función visual alterada y sólo del 5,3% de los niños con la función visual normal. Estos niños comenten más errores en la lectura (p<0,001) con un mayor número de no palabras (3,09±5,20) en comparación con los niños con la función visual normal (1,44±3,09). Comenten también más omisiones y adiciones de letras y confusiones de grafema, teniendo dificultades en el análisis global de la palabra. Se propone un modelo de orientación para los profesores.
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A utilização das TIC ocupam um lugar cada vez mais importante nas nossas escolas, marcado sobretudo pela evolução das tecnologias e pela utilização em contexto educativo de muitas ferramentas da Web 2.0. Esse facto é muito notório na disciplina de Educação Visual e Tecnológica, de carácter eminentemente prático, onde é permitido explorar várias ferramentas digitais para abordagem de conteúdos da disciplina e para a criação de produtos gráficos e plásticos. Com o aparecimento da Web 2.0 e a disponibilização de milhares de novas ferramentas digitais aos utilizadores da Internet, estimula-se um interesse cada vez maior na adoção de metodologias e estratégias com recurso a estes media e que suportem uma aprendizagem mais eficaz e motivadora para os alunos, articulando-se os suportes tradicionais de EVT com os novos media digitais. Neste contexto, o presente estudo é o resultado duma investigação-ação realizada no âmbito do Programa Doutoral em Multimédia em Educação da Universidade de Aveiro onde se implementou a integração de ferramentas da Web, Web 2.0 e Software Livre em contexto educativo na disciplina de EVT, na qual poderiam ser utilizadas tanto as técnicas tradicionais de realização mais usuais na disciplina como a integração e articulação com as ferramentas digitais, suportadas por software livre (e outros de utilização gratuita), a Web e a Web 2.0 para suporte ao ensino e aprendizagem dos diversos conteúdos e áreas de exploração da disciplina. Este estudo, desenhado em três ciclos, envolveu num primeiro momento a constituição de uma comunidade de prática de professores alargada, sendo criadas seis turmas de formação que reuniram um total de 112 professores que pretendiam integrar as ferramentas digitais em EVT. Para além da pesquisa, análise, seleção e catalogação destas 430 ferramentas digitais recenseadas, produziram-se 371 manuais de apoio à utilização das mesmas, sendo estes recursos disponibilizados no espaço do EVTdigital. Num segundo ciclo, decorrente da avaliação realizada, foi criada a distribuição EVTux para simplificar o acesso e utilização das ferramentas digitais em contexto de EVT. Finalmente, o terceiro ciclo, decorre da eliminação da disciplina de EVT do currículo do 2º ciclo do ensino básico e a sua substituição por duas novas disciplinas, tendo-se realizada a respetiva análise de conteúdo das metas curriculares e produzido a aplicação As ferramentas digitais do Mundo Visual, concebida para contextualizar e indexar as ferramentas digitais selecionadas para a nova disciplina de Educação Visual.Os resultados deste estudo apontam claramente para a possibilidade de integrar na disciplina de Educação Visual e Tecnológica (ou no presente momento, em Educação Visual) ferramentas digitais para abordagem aos conteúdos e áreas de exploração, bem como a possibilidade de se constituírem facilmente comunidades de prática (como foi o caso) que possam colaborar na catalogação destas ferramentas no contexto específico da disciplina e para a necessidade sentida pelos professores em obter informação e formação que os possa atualizar quanto à integração das TIC no currículo. Apresentam-se, ainda, as limitações deste estudo que passaram sobretudo pelo impacto negativo que a eliminação da disciplina provocou na motivação dos docentes e a sua consequente participação no decorrer de algumas fases do trabalho, e ainda da dificuldade de gestão de uma equipa de professores colaboradores tão numerosa e diversificada. Nesse sentido, são também apresentadas sugestões para estudos futuros.
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Four Ss were run in a visual span of apprehension experiment to determine whether second choices made following incorrect first responses are at the chance level, as implied by various high threshold models proposed for this situation. The relationships between response biases on first and second choices, and between first choice biases on trials with two or three possible responses, were also examined in terms of Luce's (1959) choice theory. The results were: (a) second choice performance in this task appears to be determined by response bias alone, i.e., second choices were at the chance level; (b)first and second choice response biases were not related according to Luce's choice axiom; and (c) the choice axiom predicted with reasonable accuracy the relationships between first choice response biases corresponding to trials with different numbers of possible response alternatives. © 1967 Psychonomic Society, Inc.
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Este estudo pretendeu examinar a importância dos estímulos auditivo (interpre-tação vocal do cantor) e visual (expressão facial do cantor) na perceção de emo-ções pelo público de uma performance de canto. Para tal, foram gravados, atra-vés de vídeo e áudio, dois cantores a interpretar pequenas frases melódicas com a intenção de expressar, isoladamente, as seis emoções básicas: alegria, tristeza, raiva, medo, surpresa e nojo. Para validar a expressividade dos canto-res, foi medida, através de eletromiografia, a atividade dos músculos faciais du-rante a performance da emoção e foram apresentadas as gravações áudio a um painel de especialistas que as caracterizaram em termos acústicos. Com base nas gravações audiovisuais dos cantores, foi criado um teste percetual no qual se pretendia que o ouvinte reconhecesse a emoção comunicada a partir apenas do áudio, apenas do vídeo, ou ambos. Comparando as respostas dadas, os re-sultados evidenciaram que o estímulo visual é mais eficaz do que o auditivo, e que a junção dos dois estímulos é a modalidade mais eficiente na perceção de emoções pelo público de uma performance de canto.
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Increasing the size of training data in many computer vision tasks has shown to be very effective. Using large scale image datasets (e.g. ImageNet) with simple learning techniques (e.g. linear classifiers) one can achieve state-of-the-art performance in object recognition compared to sophisticated learning techniques on smaller image sets. Semantic search on visual data has become very popular. There are billions of images on the internet and the number is increasing every day. Dealing with large scale image sets is intense per se. They take a significant amount of memory that makes it impossible to process the images with complex algorithms on single CPU machines. Finding an efficient image representation can be a key to attack this problem. A representation being efficient is not enough for image understanding. It should be comprehensive and rich in carrying semantic information. In this proposal we develop an approach to computing binary codes that provide a rich and efficient image representation. We demonstrate several tasks in which binary features can be very effective. We show how binary features can speed up large scale image classification. We present learning techniques to learn the binary features from supervised image set (With different types of semantic supervision; class labels, textual descriptions). We propose several problems that are very important in finding and using efficient image representation.
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Dissertação apresentada para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Ciências da Educação – Especialização em Supervisão Pedagógica.
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Visual recognition is a fundamental research topic in computer vision. This dissertation explores datasets, features, learning, and models used for visual recognition. In order to train visual models and evaluate different recognition algorithms, this dissertation develops an approach to collect object image datasets on web pages using an analysis of text around the image and of image appearance. This method exploits established online knowledge resources (Wikipedia pages for text; Flickr and Caltech data sets for images). The resources provide rich text and object appearance information. This dissertation describes results on two datasets. The first is Berg’s collection of 10 animal categories; on this dataset, we significantly outperform previous approaches. On an additional set of 5 categories, experimental results show the effectiveness of the method. Images are represented as features for visual recognition. This dissertation introduces a text-based image feature and demonstrates that it consistently improves performance on hard object classification problems. The feature is built using an auxiliary dataset of images annotated with tags, downloaded from the Internet. Image tags are noisy. The method obtains the text features of an unannotated image from the tags of its k-nearest neighbors in this auxiliary collection. A visual classifier presented with an object viewed under novel circumstances (say, a new viewing direction) must rely on its visual examples. This text feature may not change, because the auxiliary dataset likely contains a similar picture. While the tags associated with images are noisy, they are more stable when appearance changes. The performance of this feature is tested using PASCAL VOC 2006 and 2007 datasets. This feature performs well; it consistently improves the performance of visual object classifiers, and is particularly effective when the training dataset is small. With more and more collected training data, computational cost becomes a bottleneck, especially when training sophisticated classifiers such as kernelized SVM. This dissertation proposes a fast training algorithm called Stochastic Intersection Kernel Machine (SIKMA). This proposed training method will be useful for many vision problems, as it can produce a kernel classifier that is more accurate than a linear classifier, and can be trained on tens of thousands of examples in two minutes. It processes training examples one by one in a sequence, so memory cost is no longer the bottleneck to process large scale datasets. This dissertation applies this approach to train classifiers of Flickr groups with many group training examples. The resulting Flickr group prediction scores can be used to measure image similarity between two images. Experimental results on the Corel dataset and a PASCAL VOC dataset show the learned Flickr features perform better on image matching, retrieval, and classification than conventional visual features. Visual models are usually trained to best separate positive and negative training examples. However, when recognizing a large number of object categories, there may not be enough training examples for most objects, due to the intrinsic long-tailed distribution of objects in the real world. This dissertation proposes an approach to use comparative object similarity. The key insight is that, given a set of object categories which are similar and a set of categories which are dissimilar, a good object model should respond more strongly to examples from similar categories than to examples from dissimilar categories. This dissertation develops a regularized kernel machine algorithm to use this category dependent similarity regularization. Experiments on hundreds of categories show that our method can make significant improvement for categories with few or even no positive examples.
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The purpose of this study was to examine the relationship between visual acuity and the two components of conceptual tempo, response accuracy and response latency. Subjects were chosen at random. Each subject was then administered a test of conceptual tempo, the Matching Familiar Figures Test (MFFT) and a test of visual acuity, the Snellen. The only significant relationship found was that between response accuracy and near visual acuity. Subjects with superior visual acuity made significantly fewer errors than did those with average or inferior acuity. It was concluded that visual acuity is an important determinant of MFFT performance. Based on these results, it was recommended that further research examine the relationship between visual acuity and other psychometric measures containing a visual component.
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This study investigates if less skilled readers suffer from deficits in echoic memory, which may be responsible for limiting the progress of reading acquisition. Serial recall performance in auditory, visual, and noisy conditions was used to assess echoic memory differences between skilled and less skilled readers. Both groups showed the typical modality effect, demonstrating that each had a functioning echoic memory. Less skilled readers performed more weakly than skilled readers on noisy serial recall, suggesting that the recall of less skilled readers is more vulnerable to interference than the recall of skilled readers. Nonword repetition performance indicated that all participants had reduced recall as a function of word complexity and word length. No difference between reading groups was found on this task; however, as nonword repetition and size of modality effect did not correlate, this task may not be a measure of echoic memory.
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The production and perception of music is a multimodal activity involving auditory, visual and conceptual processing, integrating these with prior knowledge and environmental experience. Musicians utilise expressive physical nuances to highlight salient features of the score. The question arises within the literature as to whether performers’ non-technical, non-sound-producing movements may be communicatively meaningful and convey important structural information to audience members and co-performers. In the light of previous performance research (Vines et al., 2006, Wanderley, 2002, Davidson, 1993), and considering findings within co-speech gestural research and auditory and audio-visual neuroscience, this thesis examines the nature of those movements not directly necessary for the production of sound, and their particular influence on audience perception. Within the current research 3D performance analysis is conducted using the Vicon 12- camera system and Nexus data-processing software. Performance gestures are identified as repeated patterns of motion relating to music structure, which not only express phrasing and structural hierarchy but are consistently and accurately interpreted as such by a perceiving audience. Gestural characteristics are analysed across performers and performance style using two Chopin preludes selected for their diverse yet comparable structures (Opus 28:7 and 6). Effects on perceptual judgements of presentation modes (visual-only, auditory-only, audiovisual, full- and point-light) and viewing conditions are explored. This thesis argues that while performance style is highly idiosyncratic, piano performers reliably generate structural gestures through repeated patterns of upper-body movement. The shapes and locations of phrasing motions are identified particular to the sample of performers investigated. Findings demonstrate that despite the personalised nature of the gestures, performers use increased velocity of movements to emphasise musical structure and that observers accurately and consistently locate phrasing junctures where these patterns and variation in motion magnitude, shape and velocity occur. By viewing performance motions in polar (spherical) rather than cartesian coordinate space it is possible to get mathematically closer to the movement generated by each of the nine performers, revealing distinct patterns of motion relating to phrasing structures, regardless of intended performance style. These patterns are highly individualised both to each performer and performed piece. Instantaneous velocity analysis indicates a right-directed bias of performance motion variation at salient structural features within individual performances. Perceptual analyses demonstrate that audience members are able to accurately and effectively detect phrasing structure from performance motion alone. This ability persists even for degraded point-light performances, where all extraneous environmental information has been removed. The relative contributions of audio, visual and audiovisual judgements demonstrate that the visual component of a performance does positively impact on the over- all accuracy of phrasing judgements, indicating that receivers are most effective in their recognition of structural segmentations when they can both see and hear a performance. Observers appear to make use of a rapid online judgement heuristics, adjusting response processes quickly to adapt and perform accurately across multiple modes of presentation and performance style. In line with existent theories within the literature, it is proposed that this processing ability may be related to cognitive and perceptual interpretation of syntax within gestural communication during social interaction and speech. Findings of this research may have future impact on performance pedagogy, computational analysis and performance research, as well as potentially influencing future investigations of the cognitive aspects of musical and gestural understanding.
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É do conhecimento geral de que, hoje em dia, a tecnologia evolui rapidamente. São criadas novas arquitecturas para resolver determinadas limitações ou problemas. Por vezes, essa evolução é pacífica e não requer necessidade de adaptação e, por outras, essa evolução pode Implicar mudanças. As linguagens de programação são, desde sempre, o principal elo de comunicação entre o programador e o computador. Novas linguagens continuam a aparecer e outras estão sempre em desenvolvimento para se adaptarem a novos conceitos e paradigmas. Isto requer um esforço extra para o programador, que tem de estar sempre atento a estas mudanças. A Programação Visual pode ser uma solução para este problema. Exprimir funções como módulos que recebem determinado Input e retomam determinado output poderá ajudar os programadores espalhados pelo mundo, através da possibilidade de lhes dar uma margem para se abstraírem de pormenores de baixo nível relacionados com uma arquitectura específica. Esta tese não só mostra como combinar as capacidades do CeII/B.E. (que tem uma arquitectura multiprocessador heterogénea) com o OpenDX (que tem um ambiente de programação visual), como também demonstra que tal pode ser feito sem grande perda de performance. ABSTRACT; lt is known that nowadays technology develops really fast. New architectures are created ln order to provide new solutions for different technology limitations and problems. Sometimes, this evolution is pacific and there is no need to adapt to new technologies, but things also may require a change every once ln a while. Programming languages have always been the communication bridge between the programmer and the computer. New ones keep coming and other ones keep improving ln order to adapt to new concepts and paradigms. This requires an extra-effort for the programmer, who always needs to be aware of these changes. Visual Programming may be a solution to this problem. Expressing functions as module boxes which receive determined Input and return determined output may help programmers across the world by giving them the possibility to abstract from specific low-level hardware issues. This thesis not only shows how the CeII/B.E. (which has a heterogeneous multi-core architecture) capabilities can be combined with OpenDX (which has a visual programming environment), but also demonstrates that lt can be done without losing much performance.
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Dissertação de Mestrado apresentada ao Instituto Superior de Psicologia Aplicada para obtenção de grau de Mestre na especialidade de Psicologia Clínica.
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In 2010, the American Association of State Highway and Transportation Officials (AASHTO) released a safety analysis software system known as SafetyAnalyst. SafetyAnalyst implements the empirical Bayes (EB) method, which requires the use of Safety Performance Functions (SPFs). The system is equipped with a set of national default SPFs, and the software calibrates the default SPFs to represent the agency’s safety performance. However, it is recommended that agencies generate agency-specific SPFs whenever possible. Many investigators support the view that the agency-specific SPFs represent the agency data better than the national default SPFs calibrated to agency data. Furthermore, it is believed that the crash trends in Florida are different from the states whose data were used to develop the national default SPFs. In this dissertation, Florida-specific SPFs were developed using the 2008 Roadway Characteristics Inventory (RCI) data and crash and traffic data from 2007-2010 for both total and fatal and injury (FI) crashes. The data were randomly divided into two sets, one for calibration (70% of the data) and another for validation (30% of the data). The negative binomial (NB) model was used to develop the Florida-specific SPFs for each of the subtypes of roadway segments, intersections and ramps, using the calibration data. Statistical goodness-of-fit tests were performed on the calibrated models, which were then validated using the validation data set. The results were compared in order to assess the transferability of the Florida-specific SPF models. The default SafetyAnalyst SPFs were calibrated to Florida data by adjusting the national default SPFs with local calibration factors. The performance of the Florida-specific SPFs and SafetyAnalyst default SPFs calibrated to Florida data were then compared using a number of methods, including visual plots and statistical goodness-of-fit tests. The plots of SPFs against the observed crash data were used to compare the prediction performance of the two models. Three goodness-of-fit tests, represented by the mean absolute deviance (MAD), the mean square prediction error (MSPE), and Freeman-Tukey R2 (R2FT), were also used for comparison in order to identify the better-fitting model. The results showed that Florida-specific SPFs yielded better prediction performance than the national default SPFs calibrated to Florida data. The performance of Florida-specific SPFs was further compared with that of the full SPFs, which include both traffic and geometric variables, in two major applications of SPFs, i.e., crash prediction and identification of high crash locations. The results showed that both SPF models yielded very similar performance in both applications. These empirical results support the use of the flow-only SPF models adopted in SafetyAnalyst, which require much less effort to develop compared to full SPFs.