ViBee – segmentation algorithm applied to reduce video bitrates in bee weblabs

Services provided by Internet allow the creation of new distance applications, as remote laboratories (Weblabs). In this context, the broadcasting of video and images are essential for the success and effectiveness of the experiments. However, the bandwidth of the communication channel does not allo...

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Detalles Bibliográficos
Autores: Hirakawa, Andre Riyuiti, Amâncio, Silvio Miyadaira, Saraiva, Antonio Mauro, Cugnasca, Carlos Eduardo, Correa, Pedro Luiz
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2009
País:Brasil
Institución:Centro Universitário de Belo Horizonte (UNIBH)
Repositorio:Revista e-xacta
Idioma:portugués
OAI Identifier:oai:ojs.periodicos.uninove.br:article/1409
Acceso en línea:https://periodicos.uninove.br/exacta/article/view/1409
Access Level:acceso abierto
Palabra clave:Abelhas. Compressão. Segmentação. Weblab. Vídeo.
Descripción
Sumario:Services provided by Internet allow the creation of new distance applications, as remote laboratories (Weblabs). In this context, the broadcasting of video and images are essential for the success and effectiveness of the experiments. However, the bandwidth of the communication channel does not allow transmission of high-definition video in real-time, which are basic requirements for remote monitoring and actuation activities. Considering a Weblab, also called Webbee, through which it is intended to analyze the behavior of bees, these requirements become more important. Commercial videos, CODEC (MPEG4 and WMV), applied to videos of bees reduce the bitrates, as well as the quality, what makes impracticable the applications for the Webbee. Therefore, this paper presents the proposal of a new algorithm for codification of video of bees and the reduction of bitrates, maintaining the quality of the information. The algorithm includes the video segmentation process by identification, recognition and tracking of objects. The test results show an adaptation of the proposal with reduction of data equivalent to the commercial CODECs, with 93% of similarity.