Hand gesture recognition for human computer interaction : a comparative study of different image features

Hand gesture recognition for human computer interaction, being a natural way of human computer interaction, is an area of active research in computer vision and machine learning. This is an area with many different possible applications, giving users a simpler and more natural way to communicate with robots/systems interfaces, without the need for extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them to convey information or for device control. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. In this study we try to identify hand features that, isolated, respond better in various situations in human-computer interaction. The extracted features are used to train a set of classifiers with the help of RapidMiner in order to find the best learner. A dataset with our own gesture vocabulary consisted of 10 gestures, recorded from 20 users was created for later processing. Experimental results show that the radial signature and the centroid distance are the features that when used separately obtain better results, with an accuracy of 91% and 90,1% respectively obtained with a Neural Network classifier. These to methods have also the advantage of being simple in terms of computational complexity, which make them good candidates for real-time hand gesture recognition.

Exploring TM image texture and its relationships with biomass estimation in Rondônia, Brazilian Amazon

Many texture measures have been developed and used for improving land-cover classification accuracy, but rarely has research examined the role of textures in improving the performance of aboveground biomass estimations. The relationship between texture and biomass is poorly understood. This paper used Landsat Thematic Mapper (TM) data to explore relationships between TM image textures and aboveground biomass in Rondônia, Brazilian Amazon. Eight grey level co-occurrence matrix (GLCM) based texture measures (i.e., mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment, and correlation), associated with seven different window sizes (5x5, 7x7, 9x9, 11x11, 15x15, 19x19, and 25x25), and five TM bands (TM 2, 3, 4, 5, and 7) were analyzed. Pearson's correlation coefficient was used to analyze texture and biomass relationships. This research indicates that most textures are weakly correlated with successional vegetation biomass, but some textures are significantly correlated with mature forest biomass. In contrast, TM spectral signatures are significantly correlated with successional vegetation biomass, but weakly correlated with mature forest biomass. Our findings imply that textures may be critical in improving mature forest biomass estimation, but relatively less important for successional vegetation biomass estimation.

Strategies to regulate myopia progression with contact lenses: a review

Purpose: Higher myopic refractive errors are associated with serious ocular complications that can put visual function at risk. There is respective interest in slowing and if possible stopping myopia progression before it reaches a level associated with increased risk of secondary pathology. The purpose of this report was to review our understanding of the rationale(s) and success of contact lenses (CLs) used to reduce myopia progression. Methods: A review commenced by searching the PubMed database. The inclusion criteria stipulated publications of clinical trials evaluating the efficacy of CLs in regulating myopia progression based on the primary endpoint of changes in axial length measurements and published in peerreviewed journals. Other publications from conference proceedings or patents were exceptionally considered when no peer-review articles were available. Results: The mechanisms that presently support myopia regulation with CLs are based on the change of relative peripheral defocus and changing the foveal image quality signal to potentially interfere with the accommodative system. Ten clinical trials addressing myopia regulation with CLs were reviewed, including corneal refractive therapy (orthokeratology), peripheral gradient lenses, and bifocal (dual-focus) and multifocal lenses. Conclusions: CLs were reported to be well accepted, consistent, and safe methods to address myopia regulation in children. Corneal refractive therapy (orthokeratology) is so far the method with the largest demonstrated efficacy in myopia regulation across different ethnic groups. However, factors such as patient convenience, the degree of initial myopia, and non-CL treatments may also be considered. The combination of different strategies (i.e., central defocus, peripheral defocus, spectral filters, pharmaceutical delivery, and active lens-borne illumination) in a single device will present further testable hypotheses exploring how different mechanisms can reinforce or compete with each other to improve or reduce myopia regulation with CLs.

Land cover classification of Lago Grande de Curuai floodplain (Amazon, Brazil) using multi-sensor and image fusion techniques

Given the limitations of different types of remote sensing images, automated land-cover classifications of the Amazon várzea may yield poor accuracy indexes. One way to improve accuracy is through the combination of images from different sensors, by either image fusion or multi-sensor classifications. Therefore, the objective of this study was to determine which classification method is more efficient in improving land cover classification accuracies for the Amazon várzea and similar wetland environments - (a) synthetically fused optical and SAR images or (b) multi-sensor classification of paired SAR and optical images. Land cover classifications based on images from a single sensor (Landsat TM or Radarsat-2) are compared with multi-sensor and image fusion classifications. Object-based image analyses (OBIA) and the J.48 data-mining algorithm were used for automated classification, and classification accuracies were assessed using the kappa index of agreement and the recently proposed allocation and quantity disagreement measures. Overall, optical-based classifications had better accuracy than SAR-based classifications. Once both datasets were combined using the multi-sensor approach, there was a 2% decrease in allocation disagreement, as the method was able to overcome part of the limitations present in both images. Accuracy decreased when image fusion methods were used, however. We therefore concluded that the multi-sensor classification method is more appropriate for classifying land cover in the Amazon várzea.

Development of procedures for the design, optimization and manufacturing of customized orthopaedic and trauma implants: Geometrical/anatomical modelling from 3D medical imaging

Tese de Doutoramento (Programa Doutoral em Engenharia Biomédica)

A bio-inspired computational model for motion detection

Tese de Doutoramento (Programa Doutoral em Engenharia Biomédica)

Avaliação de vigas de madeira de Castanho tendo por base a classificação visual e ensaios não destrutivos

Dissertação de mestrado Internacional em Sustentabilidade do Ambiente Construído

Development and characterization of lipid-based nanosystems for controlled release of bioactive compounds

Tese de Doutoramento em Engenharia Química e Biológica.

O Espelho do Índio: A estética da afetividade no autorretrato da criança indígena na Fotopintura

Tese de Doutoramento em Estudos da Criança - Especialidade Comunicação Visual e Expressão Plástica

A 3D computer assisted Orthopedic Surgery Planning approach based on planar radiography

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Informática Médica)

Frequência 180: estilismo sonoro nas narrativas audiovisuais

Relatório de estágio de mestrado em Ciências da Comunicação (área de especialização em Audiovisual e Multimédia)

Reliability of the interpretation of coronary angiography by the simple visual method

OBJECTIVE: Evaluation of inter and intraobserver reproducibility of by the visual method interpretation of cineangiogram in a clinically based context. METHODS: Five interventional cardiologists analyzed 11 segments of 8 coronary cineangiograms at a two month apart sessions. The percent luminal reduction by the lesions were analyzed by two different classifications: in one (A) the lesions were graded in 0% = absent, 1-50% = mild, 51 - 69 = moderate, and > or = 70% = severe; the other classification (B) was a dichotomic one : <70% = nonsignificant and > or = 70%=significant lesions. The agreement were measured by the kappa (k) index. RESULTS: Interobserver agreement was moderate for classification A (1st measurement, k = 0.36 -- 0.63, k m = 0.49; 2nd measurement, k = 0.39-0.68, k m = 0.52) and good for classification B (1st measurement, k = 0.55-0.73, k m = 0.63; 2nd measurement, k = 0.37-0.82, k m = 0.61). Intraobserver levels of agreement were k = 0.57-0.95 for classification A and 0.62-1.0 for classification B. CONCLUSION: The higher level of reproducibility obtained by adopting the dichotomous criteria usually considered for ischemic limits demonstrates that in the present clinical context, the reliability of the simple visual method is adequate for the identification of patients with clinically significant lesions and candidates for myocardial revascularization procedures.

O autorretrato em literatura: ilustração e ruína

A aplicação ao caso literário do termo e do conceito de retrato, aqui incluindo a espécie mais tardia do autorretrato, não é hoje fluente, apesar da reconhecida permeabilidade do género a inúmeras linguagens artísticas e apesar de uma longa tradição de descrições de figura – particularmente no que toca a representação poético-retórica da beleza feminina – que recua à poesia clássica. Partindo de uma possível distinção entre autorretrato literário e variantes várias de escritas intimistas e autobiográficas com as quais delineia fronteiras nem sempre rigorosamente nítidas, é nosso propósito ilustrar, recorrendo a casos selecionados, modos de concretização verbal de autorretrato que se distanciam progressivamente de um paradigma representativo fundado na perceção e na semelhança, aproximando-se ao contrário de registos de rasura, apagamento, ruína, cegueira que questionam uma noção de identidade estabilizável em imagem (visual ou mental), encaminhando o gesto autorrepresentativo para uma meditação sobre a diferença e sobre o irreconhecimento; no limite, para uma condição fora do visível e porventura, arriscando os seus mais básicos pressupostos, para lá da representação.

Development of a semi-automatic self learning pattern recognition system for the control of electronic boards

This project was funded under the Applied Research Grants Scheme administered by Enterprise Ireland. The project was a partnership between Galway - Mayo Institute of Technology and an industrial company, Tyco/Mallinckrodt Galway. The project aimed to develop a semi - automatic, self - learning pattern recognition system capable of detecting defects on the printed circuits boards such as component vacancy, component misalignment, component orientation, component error, and component weld. The research was conducted in three directions: image acquisition, image filtering/recognition and software development. Image acquisition studied the process of forming and digitizing images and some fundamental aspects regarding the human visual perception. The importance of choosing the right camera and illumination system for a certain type of problem has been highlighted. Probably the most important step towards image recognition is image filtering, The filters are used to correct and enhance images in order to prepare them for recognition. Convolution, histogram equalisation, filters based on Boolean mathematics, noise reduction, edge detection, geometrical filters, cross-correlation filters and image compression are some examples of the filters that have been studied and successfully implemented in the software application. The software application developed during the research is customized in order to meet the requirements of the industrial partner. The application is able to analyze pictures, perform the filtering, build libraries, process images and generate log files. It incorporates most of the filters studied and together with the illumination system and the camera it provides a fully integrated framework able to analyze defects on printed circuit boards.