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The difficulties of data streams, i.e. Infinite length, the occurrence of concept-drift and the possible emergence of novel classes, are topics of high relevance in the field of recognition systems. To overcome all of these problems, the system should be updated continuously with new data while the amount of processing time should be kept small. We propose an incremental Parzen window kernel density...
This paper aims at dynamically understanding the properties of a scene from the analysis of moving object trajectories. Two different applications are proposed: the former is devoted to identify abnormal behaviors, while the latter allows to extract the \(k\) , most of the similar trajectories to the one hand-drawn by an human operator. A set of normal trajectories’ models is extracted using a novel...
This work aims to identify abnormal behaviors from the analysis of humans or vehicles' trajectories. A set of normal trajectories' prototypes is extracted by means of a novel unsupervised learning technique: the scene is adaptively partitioned into zones by using the distribution of the training set and each trajectory is represented as a sequence of symbols by taking into account positional information...
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