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.

Assessing student individual performance within PBL teams: findings from the implementation of a new mechanism

This paper reports on the experience of the implementation of a new mechanism to assess individual student contribution within project work, where students work in teams to solve a large-scale open-ended interdisciplinary project. The study takes place at the University of Minho, with first year engineering students, enrolled in the Industrial Management and Engineering (Integrated Masters) degree. The aim of this paper is to describe the main principles and procedures underlying the assessment mechanism created and also provide some feedback from its first implementation, based on the students, lecturers and tutors perceptions. For data collection, a survey was sent to all course lecturers and tutors involved in the assessment process. Students also contributed with suggestions, both on a workshop held at the end of the project and also by answering a survey on the overall satisfaction with PBL experience. Findings show a positive level of acceptance of the new mechanism by the students and also by the lecturers and tutors. The study identified the need to clarify the criteria used by the lecturers and the exact role of the tutor, as well as the need for further improvement of its features and procedures. Some recommendations are also issued regarding technical aspects related to some of the steps of the procedures, as well as the need for greater support on the adjustment and final setting of the individual grades.

Quantitative image analysis as a tool for Yarrowia lipolytica dimorphic growth evaluation in different culture media

Yarrowia lipolytica, a yeast strain with a huge biotechnological potential, capable to produce metabolites such as γ-decalactone, citric acid, intracellular lipids and enzymes, possesses the ability to change its morphology in response to environmental conditions. In the present study, a quantitative image analysis (QIA) procedure was developed for the identification and quantification of Y. lipolytica W29 and MTLY40-2P strains dimorphic growth, cultivated in batch cultures on hydrophilic (glucose and N-acetylglucosamine (GlcNAc) and hydrophobic (olive oil and castor oil) media. The morphological characterization of yeast cells by QIA techniques revealed that hydrophobic carbon sources, namely castor oil, should be preferred for both strains growth in the yeast single cell morphotype. On the other hand, hydrophilic sugars, namely glucose and GlcNAc caused a dimorphic transition growth towards the hyphae morphotype. Experiments for γ-decalactone production with MTLY40-2P strain in two distinct morphotypes (yeast single cells and hyphae cells) were also performed. The obtained results showed the adequacy of the proposed morphology monitoring tool in relation to each morphotype on the aroma production ability. The present work allowed establishing that QIA techniques can be a valuable tool for the identification of the best culture conditions for industrial processes implementation.

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.

A bio-inspired computational model for motion detection

Tese de Doutoramento (Programa Doutoral em Engenharia Biomédica)

Body image dissatisfaction and its relationship with physical activity and body mass index in Brazilian adolescents

Objective: To evaluate body image dissatisfaction and its relationship with physical activity and body mass index in a Brazilian sample of adolescents. Methods: A total of 275 adolescents (139 boys and 136 girls) between the ages of 14 and 18 years completed measures of body image dissatisfaction through the Contour Drawing Scale and current physical activity by the International Physical Activity Questionnaire. Weight and height were also measured for subsequent calculation of body mass index. Results: Boys and girls differed significantly regarding body image dissatisfaction, with girls reporting higher levels of dissatisfaction. Underweight and eutrophic boys preferred to be heavier, while those overweight preferred be thinner and, in contrast, girls desired to be thinner even when they are of normal weight. Conclusion: Body image dissatisfaction was strictly related to body mass index, but not to physical activity.

Cardiac findings in 31 patients with Noonan's syndrome

OBJECTIVE: To evaluate cardiac findings in 31 Noonan syndrome patients. METHODS: Thirty-one (18 males and 13 females)patients from 26 families affected with Noonan's syndrome were evaluated from the cardiac point of view with electrocardiography and echodopplercardiography. RESULTS: Twenty patients had some type of cardiac abnormality. The most frequent was pulmonary valve stenosis followed by hypertrophic myocardiopathy, commonly associated with valve defects. Upper deviation of the QRS axis was observed in 80% of these patients. CONCLUSION: In view of the high frequency and diversity of cardiac abnormalities present in Noonan syndrome, cardiac evaluation with electrocardiography and echocardiography should be performed in all patients diagnostically suspected of having this disease.

A cumulative risk model of child physical maltreatment potential: findings from a community-based study

"Published online before print November 20, 2015"

Automating the testing process of image processing algorithms

As digital imaging processing techniques become increasingly used in a broad range of consumer applications, the critical need to evaluate algorithm performance has become recognised by developers as an area of vital importance. With digital image processing algorithms now playing a greater role in security and protection applications, it is of crucial importance that we are able to empirically study their performance. Apart from the field of biometrics little emphasis has been put on algorithm performance evaluation until now and where evaluation has taken place, it has been carried out in a somewhat cumbersome and unsystematic fashion, without any standardised approach. This paper presents a comprehensive testing methodology and framework aimed towards automating the evaluation of image processing algorithms. Ultimately, the test framework aims to shorten the algorithm development life cycle by helping to identify algorithm performance problems quickly and more efficiently.

Variations and application conditions of the data type "Image" : the foundation of computational visualistics

Visualistics, computer science, picture syntax, picture semantics, picture pragmatics, interactive pictures

Treatment of Dyslipidemia with Statins and Physical Exercises: Recent Findings of Skeletal Muscle Responses

Statin treatment in association with physical exercise practice can substantially reduce cardiovascular mortality risk of dyslipidemic individuals, but this practice is associated with myopathic event exacerbation. This study aimed to present the most recent results of specific literature about the effects of statins and its association with physical exercise on skeletal musculature. Thus, a literature review was performed using PubMed and SciELO databases, through the combination of the keywords “statin” AND “exercise” AND “muscle”, restricting the selection to original studies published between January 1990 and November 2013. Sixteen studies evaluating the effects of statins in association with acute or chronic exercises on skeletal muscle were analyzed. Study results indicate that athletes using statins can experience deleterious effects on skeletal muscle, as the exacerbation of skeletal muscle injuries are more frequent with intense training or acute eccentric and strenuous exercises. Moderate physical training, in turn, when associated to statins does not increase creatine kinase levels or pain reports, but improves muscle and metabolic functions as a consequence of training. Therefore, it is suggested that dyslipidemic patients undergoing statin treatment should be exposed to moderate aerobic training in combination to resistance exercises three times a week, and the provision of physical training prior to drug administration is desirable, whenever possible.

Untersuchung der Laufradströmung einer Kreiselpumpe unter Teillastbedingungen mit Hilfe der particle image velocimetry

Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2009

Hand gesture spotting and recognition using HMMs and CRFs in color image sequences

Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2010

Vision-based representation and recognition of human activities in image sequences

Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2013