Mattia Daldoss

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In this paper we propose a novel method to analyze trajectories in surveillance scenarios relying on automatically learned Context-Free Grammars. Given a training corpus of trajectories associated to a set of actions, an initial processing is carried out to extract the syntactical structure of the activities; then, the rules characterizing different(More)
In this paper we propose a new method for trajectory analysis in surveillance scenarios using Context-Free Grammars. Starting from a predefined set of activities, we provide a tool to compare the incoming paths with the stored templates, analyzing the sequence of samples at a syntactic level. Using this approach it is possible to perform the matching of(More)
In this work we present a framework for physical rehabilitation, which is based on hand tracking. One particular requirement in physical rehabilitation is the capability of the patient to correctly reproduce a specific path, following an example provided by the medical staff. Currently, these assignments are typically performed manually, and a nurse or(More)
In this paper we present a system for indoor people tracking based on the combination of wearable sensors and a video analysis module. The sensor consists of an inertial platform, which provides attitude and acceleration data with a high rate. Data is fused by an Extended Kalman Filtering (EKF) to reconstruct the attitude and the accelerations experienced(More)
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