OCULUS surveillance system: Fuzzy on-line speed analysis from 2D images

Authors:
J. Albusac;D. Vallejo;J. J. Castro-Schez;L. Jimenez-Linares
Affiliations:
School of Technical Engineering, Plaza Manuel Meca 1, 13400 Almaden, Ciudad Real, Oreto Research Group, University of Castilla-la Mancha, Spain;School of Computer Science, Department of Information Technologies and Systems, Paseo de la Universidad 4, 13071 Ciudad Real, Oreto Research Group, University of Castilla-la Mancha, Spain;School of Computer Science, Department of Information Technologies and Systems, Paseo de la Universidad 4, 13071 Ciudad Real, Oreto Research Group, University of Castilla-la Mancha, Spain;School of Computer Science, Department of Information Technologies and Systems, Paseo de la Universidad 4, 13071 Ciudad Real, Oreto Research Group, University of Castilla-la Mancha, Spain
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

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Abstract

This paper presents an independent component integrated into a global surveillance system named as OCULUS. The aim of this component is to classify the speed of moving objects as normal or abnormal in order to detect anomalous events, taking into account the object class and spatio-temporal information such as locations and movements. The proposed component analyses the speed of the detected objects in real-time without needing several cameras, a 3D representation of the environment, or the estimation of precise values. Unlike other works, the proposed method does require knowing the camera parameters previously (e.g. height, angle, zoom level, etc.). The knowledge used by this component is automatically acquired by means of a learning algorithm that generates a set of highly interpretable fuzzy rules. The experimental results demonstrate that the proposed method is accurate, robust and provides a real-time analysis.