3 resultados para Local importance measure

em Acceda, el repositorio institucional de la Universidad de Las Palmas de Gran Canaria. España


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[EN]In this work local binary patterns based focus measures are presented. Local binary patterns (LBP) have been introduced in computer vision tasks like texture classification or face recognition. In applications where recognition is based on LBP, a computational saving can be achieved with the use of LBP in the focus measures. The behavior of the proposed measures is studied to test if they fulfill the properties of the focus measures and then a comparison with some well know focus measures is carried out in different scenarios.

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[EN]In visual surveillance face detection can be an important cue for initializing tracking algorithms. Recent work in psychophics hints at the importance of the local context of a face for robust detection, such as head contours and torso. This paper describes a detector that actively utilizes the idea of local context. The promise is to gain robustness that goes beyond the capabilities of traditional face detection making it particularly interesting for surveillance. The performance of the proposed detector in terms of accuracy and speed is evaluated on data sets from PETS 2000 and PETS 2003 and compared to the object-centered approach. Particular attention is paid to the role of available image resolution.

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The 2015 FRVT gender classification (GC) report evidences the problems that current approaches tackle in situations with large variations in pose, illumination, background and facial expression. The report suggests that both commercial and research solutions are hardly able to reach an accuracy over 90% for The Images of Groups dataset, a proven scenario exhibiting unrestricted or in the wild conditions. In this paper, we focus on this challenging dataset, stepping forward in GC performance by observing: 1) recent literature results combining multiple local descriptors, and 2) the psychophysics evidences of the greater importance of the ocular and mouth areas to solve this task...