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Video surveillance systems have enabled the monitoring of complex events in several places, such as airports, banks, streets, schools, industries, among others. Due to the massive amount of multimedia data acquired by video cameras, traditional visual inspection by human operators is a very tedious and time consuming task, whose performance is affected by fatigue and stress. A challenge is to develop...
Gender recognition from face images is a challenging problem with applications in various knowledge domains, such as biometrics, security and surveillance, human-computer interaction, among others. In this work, we propose and evaluate a novel method for gender recognition based on a geometric descriptor constructed from a pre-defined face shape model. The proposed approach, tested on four different...
Automatic data classification is a computationally intensive task that presents variable precision and is considerably sensitive to the classifier configuration and to data representation, particularly for evolving data sets. Some of these issues can best be handled by methods that support users’ control over the classification steps. In this paper, we propose a visual data classification methodology...
One of the constant challenges in image analysis is to improve the process for obtaining distinctive object characteristics. Feature descriptors usually demand high dimensionality to adequately represent the objects of interest. The higher the dimensionality, the greater the consumption of resources such as memory space and computational time. Scale-Invariant Feature Transform (SIFT) and Speeded Up...
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