SUNAR-ED: Evend Detection in a Surveillance Network

SUNAR-ED: Detekce událostí v dohledové síti

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Chmelař Petr, Ing.
Pešek Martin, Ing.
Volf Tomáš, Ing. (DIFS)

Surveillance, event detection, computer vision, annotation, active learning.

Surveillance Network Augmented by Retrieval - Event Detection (SUNAR-ED), an open source single-camera computer vision and information-retrieval based surveillance event detection system, which is based on wide area (video) surveillance system (SUNAR). It contains state of the art and experimental methods of object tracking (OpenCV), feature extraction (MPEG-7), search (similarity, spatio-temporal) and learning (Bayes, GMM, HMM, SVM). We have deployed active learning functionality based on moving objects' trajectory statistics and shape classification using  VTApi (Video Terror Application  programming interface and methodology), a data base interface used for processing and  efficient management,  indexing, retrieval and analysis of image and video data and related metadata, which was created to unify and accelerate the intelligent vision applications development.

https://sourceforge.net/projects/sunar-ed/

Available under BUT OPEN SOURCE LICENCE Version 1.
Copyright (c) 2011 - 2012, Brno University of Technology.

Security-Oriented Research in Information Technology, MŠMT, Institucionální prostředky SR ČR (např. VZ, VC), MSM0021630528, 2007-2013, running
Tools and Methods for Video and Image Processing for the Fight against Terrorism, MV, Program bezpečnostního výzkumu České republiky 2010 - 2015, VG20102015006, 2010-2015, completed

Information and Database Systems Research Group (RG IS)

Department of Information Systems (DIFS)