Persona: Bachiller Mayoral, Margarita
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0000-0001-9122-0858
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Bachiller Mayoral
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Margarita
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Publicación On the effect of feedback in multilevel representation spaces for visual surveillance tasks(Elsevier, 2009-01) Carmona, Enrique J.; Martínez Campos, Javier; Mira Mira, José; Rincón Zamorano, Mariano; Bachiller Mayoral, Margarita; Martínez Tomás, RafaelIn this work we propose a general top–down feedback scheme between adjacent description levels to interpret video sequences. This scheme distinguishes two types of feedback: repair-oriented feedback and focus-oriented feedback. With the first it is possible to improve the system's performance and produce more reliable and consistent information, and with the second it is possible to adjust the computational load to match the aims. Finally, the general feedback scheme is used in different examples for a visual surveillance application which improved the final result of each description level by using the information in the higher adjacent level.Publicación On the effect of feedback in multilevel representation spaces for visual surveillance tasks(Elsevier, 2009-01) Carmona, Enrique J.; Martínez Campos, Javier; Mira Mira, José; Rincón Zamorano, Mariano; Bachiller Mayoral, Margarita; Martínez Tomás, RafaelIn this work we propose a general top–down feedback scheme between adjacent description levels to interpret video sequences. This scheme distinguishes two types of feedback: repair-oriented feedback and focus-oriented feedback. With the first it is possible to improve the system's performance and produce more reliable and consistent information, and with the second it is possible to adjust the computational load to match the aims. Finally, the general feedback scheme is used in different examples for a visual surveillance application which improved the final result of each description level by using the information in the higher adjacent level.Publicación A block-based model for monitoring of human activity(Elsevier, 2011-03) Folgado Zuñiga, Encarnación; Carmona, Enrique J.; Rincón Zamorano, Mariano; Bachiller Mayoral, MargaritaThe study of human activity is applicable to a large number of science and technology fields, such as surveillance, biomechanics or sports applications. This article presents BB6-HM, a block-based human model for real-time monitoring of a large number of visual events and states related to human activity analysis, which can be used as components of a library to describe more complex activities in such important areas as surveillance, for example, luggage at airports, clients’ behaviour in banks and patients in hospitals. BB6-HM is inspired by the proportionality rules commonly used in Visual Arts, i.e., for dividing the human silhouette into six rectangles of the same height. The major advantage of this proposal is that analysis of the human can be easily broken down into regions, so that we can obtain information of activities. The computational load is very low, so it is possible to define a very fast implementation. Finally, this model has been applied to build classifiers for the detection of primitive events and visual attributes using heuristic rules and machine learning techniques.Publicación A block-based model for monitoring of human activity(Elsevier, 2011-03) Folgado Zuñiga, Encarnación; Carmona, Enrique J.; Rincón Zamorano, Mariano; Bachiller Mayoral, MargaritaThe study of human activity is applicable to a large number of science and technology fields, such as surveillance, biomechanics or sports applications. This article presents BB6-HM, a block-based human model for real-time monitoring of a large number of visual events and states related to human activity analysis, which can be used as components of a library to describe more complex activities in such important areas as surveillance, for example, luggage at airports, clients’ behaviour in banks and patients in hospitals. BB6-HM is inspired by the proportionality rules commonly used in Visual Arts, i.e., for dividing the human silhouette into six rectangles of the same height. The major advantage of this proposal is that analysis of the human can be easily broken down into regions, so that we can obtain information of activities. The computational load is very low, so it is possible to define a very fast implementation. Finally, this model has been applied to build classifiers for the detection of primitive events and visual attributes using heuristic rules and machine learning techniques.