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.

Escola, democracia e autonomia: uma análise das políticas e práticas no cotidiano escolar

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Personalidade e bem-estar subjetivo na excelência profissional: validação de escalas junto de gestores portugueses

O presente estudo teve como objetivo a validação da Satisfaction With Life Scale (SWLS; Diener, Emmons, Larsen, & Griffin, 1985) e da Core Self-Evaluations Scale (CSES; Judge, Erez, Bono, & Thoresen, 2003) junto de gestores empresariais portugueses (N = 108). A escala SWLS avalia a componente cognitiva do bem-estar psicológico, isto é, a satisfação percebida face à qualidade das condições de vida. A CSES, centrada na valoração básica que a pessoa faz do seu self, abarca quatro dimensões de personalidade: autoestima, autoeficácia generalizada, neuroticismo e lócus de controlo. Os resultados encontrados sugerem que ambos os instrumentos apresentam índices adequados de precisão e que os constructos iniciais definidos pelos autores se mantêm parcialmente na estrutura dimensional das escalas nesta amostra portuguesa, havendo maior proximidade na SWLS. Foi observada, ainda, uma correlação positiva e estatisticamente significativa entre traços de personalidade avaliados pela CSES e a satisfação com a vida avaliada pela SWLS, em particular relativamente aos itens reportados à perceção de autoeficácia.

Career barriers influencing career success: A focus on academics’ perceptions and experiences

Purpose – Few research has addressed the factors that undermine people’s subjective perceptions of career success. Hence, the purpose of this paper is to further illuminate the issue of career barriers in perceptions of career success for a specific group of professionals: academics. Design/methodology/approach – This study adopts an interpretative-social constructionist methodology. Complementarily, it was employed a phenomenological method in data gathering and analysis – with the use of in-depth interviews and a theme analysis. The research was undertaken with a group of 87 Portuguese academics of both sexes and in different stages of their academic careers. Findings – The findings pinpoint the existence of multi-level barriers encountered by the academics when trying to succeed in their careers. The interviewees mentioned particularly the organizational-professional career barriers pertaining to three general themes: poor collegiality and workplace relationships; the lack of organizational support and employment precariousness; and the career progression standards and expectations. At the individual life cycle level the interviewees referred to the theme of finding balance; at the same time, the gender structure was also a theme mentioned as an important career barrier in career success, particularly by the women interviewed. Research limitations/implications – One of the limitations of this research is related to the impossibility of generalizability of its findings for the general population. Nevertheless, the researcher provides enough detail that grants the reader with the ability to judge of its similarity to other research contexts. Practical implications – This research highlights the role played by distinct career barriers for a specific professional group: academics. This has implications for higher education policy-makers and for human resources managers in higher education institutions. Originality/value – The current study extends the literature on career success by offering detailed anecdotal evidence on how negative work experiences might hinder career success. This research shows that to understand career barriers to success it is useful to consider multi-level factors: organizational-level factors (e.g. poor collegiality and workplace relationships); individual-level factors (e.g. life-cycle factors such as age/career stage); and structural-level factors (e.g. gender).

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

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