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.

Hand gesture recognition system based in computer vision and machine learning

"Lecture notes in computational vision and biomechanics series, ISSN 2212-9391, vol. 19"

Generic system for human-computer gesture interaction: applications on sign language recognition and robotic soccer refereeing

Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for human-computer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of visionbased interaction systems could be the same for all applications and thus facilitate the implementation. For hand posture recognition, a SVM (Support Vector Machine) model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM (Hidden Markov Model) model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications. To validate the proposed framework two applications were implemented. The first one is a real-time system able to interpret the Portuguese Sign Language. The second one is an online system able to help a robotic soccer game referee judge a game in real time.

Vision-based portuguese sign language recognition system

Vision-based hand gesture recognition is an area of active current research in computer vision and machine learning. Being a natural way of human interaction, it is an area where many researchers are working on, with the goal of making human computer interaction (HCI) easier and natural, without the need for any extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them, for example, to convey information. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. Hand gestures are a powerful human communication modality with lots of potential applications and in this context we have sign language recognition, the communication method of deaf people. Sign lan- guages are not standard and universal and the grammars differ from country to coun- try. In this paper, a real-time system able to interpret the Portuguese Sign Language is presented and described. Experiments showed that the system was able to reliably recognize the vowels in real-time, with an accuracy of 99.4% with one dataset of fea- tures and an accuracy of 99.6% with a second dataset of features. Although the im- plemented solution was only trained to recognize the vowels, it is easily extended to recognize the rest of the alphabet, being a solid foundation for the development of any vision-based sign language recognition user interface system.

Enrollment time as a requirement for biometric hand recognition systems

Biometric systems are increasingly being used as a means for authentication to provide system security in modern technologies. The performance of a biometric system depends on the accuracy, the processing speed, the template size, and the time necessary for enrollment. While much research has focused on the first three factors, enrollment time has not received as much attention. In this work, we present the findings of our research focused upon studying user’s behavior when enrolling in a biometric system. Specifically, we collected information about the user’s availability for enrollment in respect to the hand recognition systems (e.g., hand geometry, palm geometry or any other requiring positioning the hand on an optical scanner). A sample of 19 participants, chosen randomly apart their age, gender, profession and nationality, were used as test subjects in an experiment to study the patience of users enrolling in a biometric hand recognition system.

Contribution of the evaluation strategy and the use of hearing protection for the uncertainty associated with occupational exposure to noise

Doctoral Thesis for PhD degree in Industrial and Systems Engineering

Da prova: na atuação policial e no âmbito da infração tributária

Relatório de atividade profissional de mestrado em Direito Judiciário

Tribunais nacionais e tutela jurisdicional efetiva: da cooperação à integração judiciária no contencioso da união europeia

Tese de Doutoramento em Ciências Jurídicas (área de especialização em Ciências Jurídicas Públicas).

Antifungal action of three (Z)-5-amino-N'-aryl-1-methyl-1H-imidazole-4-carbohydrazonamides

[Excerpt] The incidence of fungal infections has greatly increased in patients under sustained immunosuppression with considerable risk associated. Difficulties regarding prompt diagnosis and the limited therapeutic options dictate high mortality rates. Available antifungals display substantial toxicity, a predictable consequence of the cellular structure of the organisms involved, reduced spectrum of activity, and drug interactions. Our group had previously identified three (Z)-5-amino-N'-aryl-1-methyl-1H-imidazole-4-carbohydrazonamides 1 [aryl= phenyl (1a), 4-fluorophenyl (1b), 3fluorophenyl (1c)] as potent antifungal agents.1 (...)

Expressão e caracterização de uma lectina recombinante de interesse biomédico

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Engenharia Clínica)

The cystic fibrosis microbiome in an ecological perspective and its impact in antibiotic therapy

The recent focus on the cystic fibrosis (CF) complex microbiome has led to the recognition that the microbes can interact between them and with the host immune system, affecting the disease progression and treatment routes. Although the main focus remains on the interactions between traditional pathogens, growing evidence supports the contribution and the role of emergent species. Understanding the mechanisms and the biological effects involved in polymicrobial interactions may be the key to improve effective therapies and also to define new strategies for disease control. This review focuses on the interactions between microbe-microbe and host-microbe, from an ecological point of view, discussing their impact on CF disease progression. There are increasing indications that these interactions impact the success of antimicrobial therapy. Consequently, a new approach where therapy is personalized to patients by taking into account their individual CF microbiome is suggested.

COST Action TU1406: eBook of the 1st Workshop Meeting

COST Action TU1406 aims to address the European economic and societal needs by standardizing the condition assessment and maintenance level of roadway bridges. Currently, bridge quality control plans vary from country to country and, in some cases, within the same country. This therefore urges the establishment of a European guideline to surpass the lack of a standard methodology to assess bridge condition and to define quality control plans for roadway bridges. Such a guideline will comprise specific recommendations for assessing performance indicators as well as for the definition of performance goals, bringing together different stakeholders (e.g. universities, institutes, operators, consultants and owners) from various scientific disciplines (e.g. on-site testing, visual inspection, structural engineering, sustainability, etc.) in order to establish a common transnational language. COST Action TU1406 Workshops aim to facilitate the exchange of ideas and experiences between active researchers and practitioners as well as to stimulate discussions on new and emerging issues in line with the conference topics. This first Workshop essentially focuses on WG1 issues, namely, intends to address performance indicators, how these are assessed (e.g. visual inspection, nondestructive tests and monitoring systems), with what frequency and what values are generally obtained. The main outcomes, given in this eBook, were really important, not only for WG1 developments, but also for all the other WGs and for the Action itself.

Forecasting human entrances at a commercial store using facial recognition data

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

Hand gesture recognition system based in computer vision and machine learning: Applications on human-machine interaction

Tese de Doutoramento em Engenharia de Eletrónica e de Computadores

“PhenoWorld”: a new multidimensional strategy for studying behaviour in rodents

Tese de Doutoramento em Ciências da Saúde