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.

An object-oriented model for rapid prototyping of data path/control systems - a case study

Publicado em "Information control in manufacturing 1998 : (INCOM'98) : advances in industrial engineering : a proceedings volume from the 9th IFAC Symposium, Nancy-Metz, France, 24-26 June 1998. Vol. 2"

Object-oriented inheritance of statecharts for control applications

This paper discusses how object-oriented iuheritance can be re-interpreted if statecharts are used for modelling the dynamic behaviour of an object. The support of inheritance of statecharts allows the improvement of systems' development by easing the reutilization of parts of already developed euccessful systems, aad by promoting the iterative and continuous models' refinement advocated by the operatioaal approach. Statechart is the formalism used within UML to specify reactive state.based behaviours. This paper covers the use of statecharts within the modelling of embedded systems for industrial control applxications, where performance and memory usage are main concerns.

FPGA field oriented control of an axial flux motor-in-wheel

This paper presents the design and the prototype implementation of a three-phase power inverter developed to drive a motor-in-wheel. The control system is implemented in a FPGA (Field Programmable Gate Array) device. The paper describes the Field Oriented Control (FOC) algorithm and the Space Vector Modulation (SVM) technique that were implemented. The control platform uses a Spartan-3E FPGA board, programmed with Verilog language. Simulation and experimental results are presented to validate the developed system operation under different load conditions. Finally are presented conclusions based on the experimental results.

Field oriented control of an axial flux permanent magnet synchronous motor for traction solutions

Electric Vehicles (EVs) are increasingly used nowadays, and different powertrain solutions can be adopted. This paper describes the control system of an axial flux Permanent Magnet Synchronous Motor (PMSM) for EVs powertrain. It is described the implemented Field Oriented Control (FOC) algorithm and the Space Vector Modulation (SVM) technique. Also, the mathematical model of the PMSM is presented. Both, simulation and experimental, results with different types of mechanical load are presented. The experimental results were obtained using a laboratory test bench. The obtained results are discussed.

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.

Generic system for human-computer gesture interaction

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 humancomputer 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 vision-based interaction systems can be the same for all applications and thus facilitate the implementation. In order to test the proposed solutions, three prototypes were implemented. For hand posture recognition, a SVM model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM 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.

Dynamic group formation in mobile computer supported collaborative learning environment

Forming suitable learning groups is one of the factors that determine the efficiency of collaborative learning activities. However, only a few studies were carried out to address this problem in the mobile learning environments. In this paper, we propose a new approach for an automatic, customized, and dynamic group formation in Mobile Computer Supported Collaborative Learning (MCSCL) contexts. The proposed solution is based on the combination of three types of grouping criteria: learner’s personal characteristics, learner’s behaviours, and context information. The instructors can freely select the type, the number, and the weight of grouping criteria, together with other settings such as the number, the size, and the type of learning groups (homogeneous or heterogeneous). Apart from a grouping mechanism, the proposed approach represents a flexible tool to control each learner, and to manage the learning processes from the beginning to the end of collaborative learning activities. In order to evaluate the quality of the implemented group formation algorithm, we compare its Average Intra-cluster Distance (AID) with the one of a random group formation method. The results show a higher effectiveness of the proposed algorithm in forming homogenous and heterogeneous groups compared to the random method.

Avaliação do processo de implementação de PBL num curso de engenharia informática em Moçambique: as percepções dos estudantes

O presente artigo traz uma avaliação sobre um processo de implementação do PBL que ocorreu no curso de Engenharia Informática na Faculdade de Engenharia da Universidade Eduardo Mondlane em Moçambique. Por este processo ser novo no contexto de ensino de Engenharia em Moçambique foram os desafios encontrados por parte dos docentes e estudantes relativos a implementação, coordenação e adequação do currículo a metodologia do PBL, fazendo com que o processo de implementação fosse gradual. Assim no primeiro semestre de 2014 foi implementado um processo PBL piloto envolvendo as disciplinas de Programação Orientada à Objetos 1 e Base de Dados 1, que foram disciplinas escolhidas pelo facto de seus currículos terem matérias comuns, todos desafios e comentários dados pelos estudantes foram levados em conta no desenho do segundo processo PBL para o segundo semestre de 2014 que envolveu as disciplinas de Programação Orientada à Objetos 2, Base de Dados 2 e Sistemas de Multimídia fazendo com que houvesse mais informação para o terceiro processo envolvendo as disciplinas de Engenharia de Software 1 e Programação em Web. A avaliação do processo por parte dos estudantes, veio através de inquiridos onde os estudantes fizeram chegar as suas preocupações e ideias a respeito do PBL e dos moldes em que este estava a ser implementado no currículo. O processo de implementação do PBL pode ser considerado uma experiência bem sucedida e com futuro promissor e que de certeza vai ajudar a inovar os processos de ensino de engenharia em Moçambique.

Task clustering on ETL systems – A pattern-oriented approach

Usually, data warehousing populating processes are data-oriented workflows composed by dozens of granular tasks that are responsible for the integration of data coming from different data sources. Specific subset of these tasks can be grouped on a collection together with their relationships in order to form higher- level constructs. Increasing task granularity allows for the generalization of processes, simplifying their views and providing methods to carry out expertise to new applications. Well-proven practices can be used to describe general solutions that use basic skeletons configured and instantiated according to a set of specific integration requirements. Patterns can be applied to ETL processes aiming to simplify not only a possible conceptual representation but also to reduce the gap that often exists between two design perspectives. In this paper, we demonstrate the feasibility and effectiveness of an ETL pattern-based approach using task clustering, analyzing a real world ETL scenario through the definitions of two commonly used clusters of tasks: a data lookup cluster and a data conciliation and integration cluster.

Controlador com FPGA para um motor-in-wheel CA de fluxo axial

Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e de Computadores

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

A bio-inspired computational model for motion detection

Tese de Doutoramento (Programa Doutoral em Engenharia Biomédica)