107 resultados para Cameras


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Pós-graduação em Televisão Digital: Informação e Conhecimento - FAAC

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Ciências Cartográficas - FCT

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Ciências da Motricidade - IBRC

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Engenharia Mecânica - FEIS

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Poultry facilities must provide an environment that ensures thermal comfort allowing the animal to express its genetic potential for production; and new tools are being applied to measure the thermal comfort, especially thermal cameras. The objective of this study was to evaluate the association of the surface temperature of the birds with those from the facilities, and estimate the sensible heat transfer. For this, the thermal conditions of rearing in two aviaries with different ventilation systems, during the period of March to April 2011 were recorded. The aviaries were divided into six quadrants for the registration of surface temperatures obtained using an infrared thermal camera. In each quadrant the ambient temperature, relative humidity and wind velocity during the obtention of images were also recorded. It was observed that the surface temperatures of birds are associated with the surface temperature of the rearing facilities (side curtains, roof and litter). In aviary with negative pressure higher wind speeds compared to the conventional one were recorded and; therefore, allowed a higher sensible heat transfer by birds, suggesting that this provided better conditions for thermal comfort.

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Animal behavioral parameters can be used to assess welfare status in commercial broiler breeders. Behavioral parameters can be monitored with a variety of sensing devices, for instance, the use of video cameras allows comprehensive assessment of animal behavioral expressions. Nevertheless, the development of efficient methods and algorithms to continuously identify and differentiate animal behavior patterns is needed. The objective this study was to provide a methodology to identify hen white broiler breeder behavior using combined techniques of image processing and computer vision. These techniques were applied to differentiate body shapes from a sequence of frames as the birds expressed their behaviors. The method was comprised of four stages: (1) identification of body positions and their relationship with typical behaviors. For this stage, the number of frames required to identify each behavior was determined; (2) collection of image samples, with the isolation of the birds that expressed a behavior of interest; (3) image processing and analysis using a filter developed to separate white birds from the dark background; and finally (4) construction and validation of a behavioral classification tree, using the software tool Weka (model 148). The constructed tree was structured in 8 levels and 27 leaves, and it was validated using two modes: the set training mode with an overall rate of success of 96.7%, and the cross validation mode with an overall rate of success of 70.3%. The results presented here confirmed the feasibility of the method developed to identify white broiler breeder behavior for a particular group of study. Nevertheless, more improvements in the method can be made in order to increase the validation overall rate of success. (C) 2013 Elsevier B.V. All rights reserved.