Using cloud technologies for engaging people with cultural heritage

Cultural heritage is an important asset of Europe which is largely underexplored. One of the main reasons is that the general public do not really incorporate cultural activities in their life style. Currently, curators and professionals in the heritage sector face the toughest challenges on how to attract, engage and retain visitors of heritage institutions (libraries, museums, archives and historical societies). TAG CLOUD FP7 European project seeks to overcome this situation and promote lifelong engagement with culture by personalising the visitors? cultural experiences through cloud technologies.

Optimal Piecewise Linear Function Approximation for GPU-based Applications

Many computer vision and human-computer interaction applications developed in recent years need evaluating complex and continuous mathematical functions as an essential step toward proper operation. However, rigorous evaluation of this kind of functions often implies a very high computational cost, unacceptable in real-time applications. To alleviate this problem, functions are commonly approximated by simpler piecewise-polynomial representations. Following this idea, we propose a novel, efficient, and practical technique to evaluate complex and continuous functions using a nearly optimal design of two types of piecewise linear approximations in the case of a large budget of evaluation subintervals. To this end, we develop a thorough error analysis that yields asymptotically tight bounds to accurately quantify the approximation performance of both representations. It provides an improvement upon previous error estimates and allows the user to control the trade-off between the approximation error and the number of evaluation subintervals. To guarantee real-time operation, the method is suitable for, but not limited to, an efficient implementation in modern Graphics Processing Units (GPUs), where it outperforms previous alternative approaches by exploiting the fixed-function interpolation routines present in their texture units. The proposed technique is a perfect match for any application requiring the evaluation of continuous functions, we have measured in detail its quality and efficiency on several functions, and, in particular, the Gaussian function because it is extensively used in many areas of computer vision and cybernetics, and it is expensive to evaluate.

Estimación eficiente de atributos demográficos del rostro humano en imágenes

Sin duda, el rostro humano ofrece mucha más información de la que pensamos. La cara transmite sin nuestro consentimiento señales no verbales, a partir de las interacciones faciales, que dejan al descubierto nuestro estado afectivo, actividad cognitiva, personalidad y enfermedades. Estudios recientes [OFT14, TODMS15] demuestran que muchas de nuestras decisiones sociales e interpersonales derivan de un previo análisis facial de la cara que nos permite establecer si esa persona es confiable, trabajadora, inteligente, etc. Esta interpretación, propensa a errores, deriva de la capacidad innata de los seres humanas de encontrar estas señales e interpretarlas. Esta capacidad es motivo de estudio, con un especial interés en desarrollar métodos que tengan la habilidad de calcular de manera automática estas señales o atributos asociados a la cara. Así, el interés por la estimación de atributos faciales ha crecido rápidamente en los últimos años por las diversas aplicaciones en que estos métodos pueden ser utilizados: marketing dirigido, sistemas de seguridad, interacción hombre-máquina, etc. Sin embargo, éstos están lejos de ser perfectos y robustos en cualquier dominio de problemas. La principal dificultad encontrada es causada por la alta variabilidad intra-clase debida a los cambios en la condición de la imagen: cambios de iluminación, oclusiones, expresiones faciales, edad, género, etnia, etc.; encontradas frecuentemente en imágenes adquiridas en entornos no controlados. Este de trabajo de investigación estudia técnicas de análisis de imágenes para estimar atributos faciales como el género, la edad y la postura, empleando métodos lineales y explotando las dependencias estadísticas entre estos atributos. Adicionalmente, nuestra propuesta se centrará en la construcción de estimadores que tengan una fuerte relación entre rendimiento y coste computacional. Con respecto a éste último punto, estudiamos un conjunto de estrategias para la clasificación de género y las comparamos con una propuesta basada en un clasificador Bayesiano y una adecuada extracción de características. Analizamos en profundidad el motivo de porqué las técnicas lineales no han logrado resultados competitivos hasta la fecha y mostramos cómo obtener rendimientos similares a las mejores técnicas no-lineales. Se propone un segundo algoritmo para la estimación de edad, basado en un regresor K-NN y una adecuada selección de características tal como se propuso para la clasificación de género. A partir de los experimentos desarrollados, observamos que el rendimiento de los clasificadores se reduce significativamente si los ´estos han sido entrenados y probados sobre diferentes bases de datos. Hemos encontrado que una de las causas es la existencia de dependencias entre atributos faciales que no han sido consideradas en la construcción de los clasificadores. Nuestro resultados demuestran que la variabilidad intra-clase puede ser reducida cuando se consideran las dependencias estadísticas entre los atributos faciales de el género, la edad y la pose; mejorando el rendimiento de nuestros clasificadores de atributos faciales con un coste computacional pequeño. Abstract Surely the human face provides much more information than we think. The face provides without our consent nonverbal cues from facial interactions that reveal our emotional state, cognitive activity, personality and disease. Recent studies [OFT14, TODMS15] show that many of our social and interpersonal decisions derive from a previous facial analysis that allows us to establish whether that person is trustworthy, hardworking, intelligent, etc. This error-prone interpretation derives from the innate ability of human beings to find and interpret these signals. This capability is being studied, with a special interest in developing methods that have the ability to automatically calculate these signs or attributes associated with the face. Thus, the interest in the estimation of facial attributes has grown rapidly in recent years by the various applications in which these methods can be used: targeted marketing, security systems, human-computer interaction, etc. However, these are far from being perfect and robust in any domain of problems. The main difficulty encountered is caused by the high intra-class variability due to changes in the condition of the image: lighting changes, occlusions, facial expressions, age, gender, ethnicity, etc.; often found in images acquired in uncontrolled environments. This research work studies image analysis techniques to estimate facial attributes such as gender, age and pose, using linear methods, and exploiting the statistical dependencies between these attributes. In addition, our proposal will focus on the construction of classifiers that have a good balance between performance and computational cost. We studied a set of strategies for gender classification and we compare them with a proposal based on a Bayesian classifier and a suitable feature extraction based on Linear Discriminant Analysis. We study in depth why linear techniques have failed to provide competitive results to date and show how to obtain similar performances to the best non-linear techniques. A second algorithm is proposed for estimating age, which is based on a K-NN regressor and proper selection of features such as those proposed for the classification of gender. From our experiments we note that performance estimates are significantly reduced if they have been trained and tested on different databases. We have found that one of the causes is the existence of dependencies between facial features that have not been considered in the construction of classifiers. Our results demonstrate that intra-class variability can be reduced when considering the statistical dependencies between facial attributes gender, age and pose, thus improving the performance of our classifiers with a reduced computational cost.

REFLEXOS INDIVIDUAIS DO USO PESSOAL E EXCESSIVO DE COMUNICADORES INSTANTÂNEOS NO AMBIENTE DE TRABALHO

A Internet está inserida no cotidiano do indivíduo, e torna-se cada vez mais acessível por meio de diferentes tipos de dispositivos. Com isto, diversos estudos foram realizados com o intuito de avaliar os reflexos do seu uso excessivo na vida pessoal, acadêmica e profissional. Esta dissertação buscou identificar se a perda de concentração e o isolamento social são alguns dos reflexos individuais que o uso pessoal e excessivo de aplicativos de comunicação instantânea podem resultar no ambiente de trabalho. Entre as variáveis selecionadas para avaliar os aspectos do uso excessivo de comunicadores instantâneos tem-se a distração digital, o controle reduzido de impulso, o conforto social e a solidão. Através de uma abordagem de investigação quantitativa, utilizaram-se escalas aplicadas a uma amostra de 283 pessoas. Os dados foram analisados por meio de técnicas estatísticas multivariadas como a Análise Fatorial Exploratória e para auferir a relação entre as variáveis, a Regressão Linear Múltipla. Os resultados deste estudo confirmam que o uso excessivo de comunicadores instantâneos está positivamente relacionado com a perda de concentração, e a variável distração digital exerce uma influência maior do que o controle reduzido de impulso. De acordo com os resultados, não se podem afirmar que a solidão e o conforto social exercem relações com aumento do isolamento social, devido à ausência do relacionamento entre os construtos.

Detección automática con snakes y representación 3D sobre imágenes cerebrales

Comunicación presentada en la VI Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA'95), Alicante, 15-17 noviembre 1995.

Environmental and Occupational Optometry. Lesson 8 (Course 2013-2014)

Tema 8: Pantallas de visualización de datos. Actividad voluntaria nº 5.

Towards a real-time 3D object recognition pipeline on mobile GPGPU computing platforms using low-cost RGB-D sensors

In this project, we propose the implementation of a 3D object recognition system which will be optimized to operate under demanding time constraints. The system must be robust so that objects can be recognized properly in poor light conditions and cluttered scenes with significant levels of occlusion. An important requirement must be met: the system must exhibit a reasonable performance running on a low power consumption mobile GPU computing platform (NVIDIA Jetson TK1) so that it can be integrated in mobile robotics systems, ambient intelligence or ambient assisted living applications. The acquisition system is based on the use of color and depth (RGB-D) data streams provided by low-cost 3D sensors like Microsoft Kinect or PrimeSense Carmine. The range of algorithms and applications to be implemented and integrated will be quite broad, ranging from the acquisition, outlier removal or filtering of the input data and the segmentation or characterization of regions of interest in the scene to the very object recognition and pose estimation. Furthermore, in order to validate the proposed system, we will create a 3D object dataset. It will be composed by a set of 3D models, reconstructed from common household objects, as well as a handful of test scenes in which those objects appear. The scenes will be characterized by different levels of occlusion, diverse distances from the elements to the sensor and variations on the pose of the target objects. The creation of this dataset implies the additional development of 3D data acquisition and 3D object reconstruction applications. The resulting system has many possible applications, ranging from mobile robot navigation and semantic scene labeling to human-computer interaction (HCI) systems based on visual information.

The Use of Nudges in Exergames to Moderate Player Exertion

Exergames are digital games with a physical exertion component. Exergames can help motivate fitness in people not inclined toward exercise. However, players of exergames sometimes over-exert, risking adverse health effects. These players must be told to slow down, but doing so may distract them from gameplay and diminish their desire to keep exercising. In this thesis we apply the concept of nudges—indirect suggestions that gently push people toward a desired behaviour—to keeping exergame players from over-exerting. We describe the effective use of nudges through a set of four design principles: natural integration, comprehension, progression, and multiple channels. We describe two exergames modified to use nudges to persuade players to slow down, and describe the studies evaluating the use of nudges in these games. PlaneGame shows that nudges can be as effective as an explicit textual display to control player over-exertion. Gekku Race demonstrates that nudges are not necessarily effective when players have a strong incentive to over-exert. However, Gekku Race also shows that, even in high-energy games, the power of nudges can be maintained by adding negative consequences to the nudges. We use the term "shove" to describe a nudge using negative consequences to increase its pressure. We were concerned that making players slow down would damage their immersion—the feeling of being engaged with a game. However, testing showed no loss of immersion through the use of nudges to reduce exertion. Players reported that the nudges and shoves motivated them to slow down when they were over-exerting, and fit naturally into the games.

Processo de desenho de uma aplicação para o município de Mira

Este relatório descreve as atividades desenvolvidas durante o projeto que realizei no gabinete de sistemas e informação do Município de Mira, com vista à compleição da unidade curricular HCI Project II, do Mestrado em Human Computer Interaction, da Escola Superior de Educação de Coimbra. O projeto consistiu no desenho da interação de uma aplicação móvel a criar para a Câmara Municipal de Mira, que permita apoiar o cidadão na utilização dos percursos pedonais existentes, assim como informar os Munícipes e principalmente os turistas dos acontecimentos e potencialidades do Concelho. A Câmara Municipal, apenas dispõe de uma página web que facilita a divulgação de informações e eventos, no entanto surgiu a necessidade de apoiar com rigor e especialmente a localização do cidadão na utilização dos percursos pedestres. Foi realizado todo o processo de design, onde foram aplicados os princípios e metodologias de HCI, sempre focados no utilizador. Após reunião com as partes intervenientes e depois de se definirem os objetivos do projeto, iniciei a primeira fase de estudo e pesquisa de informação relativa a aplicações existentes relacionadas com o assunto. Na fase seguinte, passei à listagem das necessidades que se pretendiam satisfazer onde se definiram os objetivos. Concluídas estas etapas, passei à fase de análise de utilizadores, onde realizei entrevistas contextuais, enumerei experiências paralelas, criei personas e defini os point of view. Com a recolha desta informação passei à fase de ideação onde criei as design directives. Posteriormente foram definidas as principais funcionalidades, foram criadas storyboards e criei um protótipo de baixa fidelidade que após ter sido validado e ajustado deu origem a um protótipo de alta fidelidade. Este protótipo foi validado, realizei o modelo visual da arquitetura de informação e o modelo da interação (flow) entre ecrãs nas principais funcionalidades. Por fim, após estar concluída a validação do protótipo de alta fidelidade foram enumerados alguns aspetos do que deveriam ser melhorados para facilitar a interação do utilizador.

Influence apart from Adoption: How Interaction between Programming and Scientific Practices Shapes Modes of Inquiry in Four Oceanography Teams

Thesis (Ph.D.)--University of Washington, 2016-06

Experience as a moderator of the media equation: the impact of flattery and praise

This study extends previous media equation research, which showed that the effects of flattery from a computer can produce the same general effects as flattery from humans. Specifically, the study explored the potential moderating effect of experience on the impact of flattery from a computer. One hundred and fifty-eight students from the University of Queensland voluntarily participated in the study. Participants interacted with a computer and were exposed to one of three kinds of feedback: praise (sincere praise), flattery (insincere praise), or control (generic feedback). Questionnaire measures assessing participants' affective state. attitudes and opinions were taken. Participants of high experience, but not low experience, displayed a media equation pattern of results, reacting to flattery from a computer in a manner congruent with peoples' reactions to flattery from other humans. High experience participants tended to believe that the computer spoke the truth, experienced more positive affect as a result of flattery, and judged the computer's performance more favourably. These findings are interpreted in light of previous research and the implications for software design in fields such as entertainment and education are considered. (C) 2004 Elsevier Ltd. All rights reserved.

Bridging technical and HCI research: Creating usable ubiquitous computing

This paper describes methods used to support collaboration and communication between practitioners, designers and engineers when designing ubiquitous computing systems. We tested methods such as “Wizard of Oz” and design games in a real domain, the dental surgery, in an attempt to create a system that is: affordable; minimally disruptive of the natural flow of work; and improves human-computer interaction. In doing so we found that such activities allowed the practitioners to be on a ‘level playing ground’ with designers and engineers. The findings we present suggest that dentists are willing to engage in detailed exploration and constructive critique of technical design possibilities if the design ideas and prototypes are presented in the context of their work practice and are of a resolution and relevance that allow them to jointly explore and question with the design time. This paper is an extension of a short paper submitted to the Participatory Design Conference, 2004.

Simulation of air traffic controllers' behaviour using the operator choice model

The Operator Choice Model (OCM) was developed to model the behaviour of operators attending to complex tasks involving interdependent concurrent activities, such as in Air Traffic Control (ATC). The purpose of the OCM is to provide a flexible framework for modelling and simulation that can be used for quantitative analyses in human reliability assessment, comparison between human computer interaction (HCI) designs, and analysis of operator workload. The OCM virtual operator is essentially a cycle of four processes: Scan Classify Decide Action Perform Action. Once a cycle is complete, the operator will return to the Scan process. It is also possible to truncate a cycle and return to Scan after each of the processes. These processes are described using Continuous Time Probabilistic Automata (CTPA). The details of the probability and timing models are specific to the domain of application, and need to be specified using domain experts. We are building an application of the OCM for use in ATC. In order to develop a realistic model we are calibrating the probability and timing models that comprise each process using experimental data from a series of experiments conducted with student subjects. These experiments have identified the factors that influence perception and decision making in simplified conflict detection and resolution tasks. This paper presents an application of the OCM approach to a simple ATC conflict detection experiment. The aim is to calibrate the OCM so that its behaviour resembles that of the experimental subjects when it is challenged with the same task. Its behaviour should also interpolate when challenged with scenarios similar to those used to calibrate it. The approach illustrated here uses logistic regression to model the classifications made by the subjects. This model is fitted to the calibration data, and provides an extrapolation to classifications in scenarios outside of the calibration data. A simple strategy is used to calibrate the timing component of the model, and the results for reaction times are compared between the OCM and the student subjects. While this approach to timing does not capture the full complexity of the reaction time distribution seen in the data from the student subjects, the mean and the tail of the distributions are similar.

Dissecting query performance in logical data models: Parsimony vs. greater ontological clarity

Even when data repositories exhibit near perfect data quality, users may formulate queries that do not correspond to the information requested. Users’ poor information retrieval performance may arise from either problems understanding of the data models that represent the real world systems, or their query skills. This research focuses on users’ understanding of the data structures, i.e., their ability to map the information request and the data model. The Bunge-Wand-Weber ontology was used to formulate three sets of hypotheses. Two laboratory experiments (one using a small data model and one using a larger data model) tested the effect of ontological clarity on users’ performance when undertaking component, record, and aggregate level tasks. The results indicate for the hypotheses associated with different representations but equivalent semantics that parsimonious data model participants performed better for component level tasks but that ontologically clearer data model participants performed better for record and aggregate level tasks.