DocumentCode :
419635
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
Volume :
1
fYear :
2004
fDate :
23-26 Aug. 2004
Firstpage :
753
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;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on
ISSN :
1051-4651
Print_ISBN :
0-7695-2128-2
Type :
conf
DOI :
10.1109/ICPR.2004.1334302
Filename :
1334302
Link To Document :
بازگشت