Title :
Architectural design issues for Bayesian contextual vision
Author :
Lombardi, P. ; Zavidovique, B.
Author_Institution :
Interactive Sensory Syst. Div., Istituto Trentino di Cultura, Trento, Italy
Abstract :
Sensor fusion technology has been so far developed for the fusion of camera and different sensors, e.g. radar, sonar, etc. The same techniques apply to integrating several vision algorithms into a multi-modular system. In this paper, we abstract our attempt on the matter and propose a uniform paradigm to integrate both "vision modules" directly observing targets (e.g. intruders in video surveillance) and "accessory modules" observing scene features that may trigger system adaptation to the current context. To be concrete, we completely develop a real example in re-designing a previous context-dependent video surveillance system.
Keywords :
Bayes methods; computer vision; feature extraction; sensor fusion; state estimation; surveillance; video signal processing; Bayesian contextual vision; accessory modules; architectural design; camera fusion; context dependent video surveillance; feature extraction; multimodular system; sensor fusion technology; state estimation; vision modules; Bayesian methods; Cameras; Computer vision; Layout; Machine vision; Radar; Sensor fusion; Sensor systems; Sonar; Video surveillance;
Conference_Titel :
Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on
Print_ISBN :
0-7695-2128-2
DOI :
10.1109/ICPR.2004.1334302