The Agent WiSARD Approach to Intelligent Active Video Surveillance Systems

The Agent WiSARD methodology for intelligent active video surveillance systems is proposed in this paper. The hybrid neurosymbolic system (called ISIDIS) is based on the integration of virtual neural sensors and BDI agents. The use of virtual neural sensors coupled with symbolic reasoning allow the system to work on different scenarios and in any light condition.

[1]  Matteo Matteucci,et al.  A revaluation of frame difference in fast and robust motion detection , 2006, VSSN '06.

[2]  Jong Bae Kim,et al.  Efficient region-based motion segmentation for a video monitoring system , 2003, Pattern Recognit. Lett..

[3]  Massimo De Gregorio,et al.  NSP: A Neuro-symbolic Processor , 2003, IWANN.

[4]  Katsushi Ikeuchi,et al.  Illumination normalization with time-dependent intrinsic images for video surveillance , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Michael Wooldridge,et al.  Reasoning about rational agents , 2000, Intelligent robots and autonomous agents.

[6]  Paolo Coraggio,et al.  Agent WiSARD: A Hybrid System for Reconstructing and Understanding Two-dimensional Geometrical Figures , 2003, HIS.

[7]  Paolo Coraggio,et al.  Agent WiSARD in a 3D World , 2005, IWINAC.

[8]  Mohan M. Trivedi,et al.  Detecting Moving Shadows: Algorithms and Evaluation , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  Nicholas R. Jennings,et al.  Intelligent agents: theory and practice , 1995, The Knowledge Engineering Review.

[10]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[11]  I. Aleksander,et al.  WISARD·a radical step forward in image recognition , 1984 .

[12]  Massimo De Gregorio Is That Portal Ghotic? A Hybrid System for Recognising Architectural Portal Shapes , 1996, MVA.

[13]  Mario Hernández-Tejera,et al.  Heuristic Algorithms for Fast and Accurate Tracking of Moving Objects in Unrestricted Environments , 2005, BVAI.