Welcome to the Computer Vision & Pattern Recognition Laboratory

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TO OUR PROFESSOR ALFREDO PETROSINO 

 

 The Computer Vision and and Pattern Recognition group is part of the Department of Science and Technology at University of Naples "Parthenope". The research envisaged covers a broad spectrum of issues related to Computer Vision and Pattern Recognition, Image Processing, and participates in a variety of applied projects, where results and know-how from those programs are exploited. Our research is focused on several mainstreams :

Computer Vision

The research is naturally focused on image analysis and understanding aspects in the large, which are at the basis of all advanced processing. Specific on multiresolution, object recognition, soft computing in image analysis, attentive vision mechanisms with applications to video surveillance, medical imaging, multimedia data treatment.

Pattern Recognition

Research in this field is mainly focused on the probabilistic models for pattern recognition, because of their interesting theoretical properties and their wide applicability in (not only) computer vision tasks. Our interest is mainly in investigating Neural Networks, Markov Random Fields and Kernel Methods. We are interested both in methodological, e.g. learning and model selection, and applicative issues, as shape classification, event detection and classification and clustering, tracking, and video surveillance. Our research is also oriented on very promising non probabilistic techniques, as Support Vector Machines.

Soft Computing

The aim of Soft Computing is to exploit the tolerance for imprecision, uncertainty, approximate reasoning, and partial truth in order to achieve tractability, robustness, and low-cost solutions for handling real-life ambiguous situations. The CVPRLab research activity aims at devising methods based on joint rough-fuzzy and fuzzy-rough computing, leading to an acceptable solution to an imprecisely/precisely formulated problem seeking for an approximate solution in the Data Mining step of the overall Knowledge Data Discovery (KDD) process.

To Our Friend Vito Di Gesù.....