학술논문
Vision-based augmentation of a sentient computing world model
Document Type
Conference
Author
Source
Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. Pattern recognition Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on. 1:724-727 Vol.1 2004
Subject
Language
ISSN
1051-4651
Abstract
This paper presents a work which integrates computer vision information obtained from calibrated cameras with location events from an office-based ultrasonic location system. Bayesian networks are used to model dependencies and reliabilities of the multi-modal variables and perform fusion. Context is represented using a world model which incorporates aspects of both the static and dynamic environment. Information from the sentient computing system is used to guide and constrain the computer vision components, which in turn enhance the accuracy and capabilities of the world model.