Bauckhage, Christian, Hanheide, Marc, Wrede, Sebastian and Sagerer, Gerhard (2004) A cognitive vision system for action recognition in office environments. In: 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004, 27 th June - 2 nd July, 2004, Washington DC.
Full content URL: http://dx.doi.org/10.1109/CVPR.2004.1315250
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Bauckhage2004-A_Cognitive_Vision_System_for_Action_Recognition_in_Office_Environments.pdf - Whole Document Restricted to Repository staff only 436kB |
Item Type: | Conference or Workshop contribution (Paper) |
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Item Status: | Live Archive |
Abstract
The emerging cognitive vision paradigm is concerned
with vision systems that evaluate, gather and integrate con-
textual knowledge for visual analysis. In reasoning about
events and structures, cognitive vision systems should rely
on multiple computations in order to perform robustly even
in noisy domains. Action recognition in an unconstrained
office environment thus provides an excellent testbed for re-
search on cognitive computer vision. In this contribution,
we present a system that consists of several computational
modules for object and action recognition. It applies atten-
tion mechanisms, visual learning and contextual as well as
probabilistic reasoning to fuse individual results and verify
their consistency. Database technologies are used for infor-
mation storage and an XML based communication frame-
work integrates all modules into a consistent architecture.
Additional Information: | The emerging cognitive vision paradigm is concerned with vision systems that evaluate, gather and integrate con- textual knowledge for visual analysis. In reasoning about events and structures, cognitive vision systems should rely on multiple computations in order to perform robustly even in noisy domains. Action recognition in an unconstrained office environment thus provides an excellent testbed for re- search on cognitive computer vision. In this contribution, we present a system that consists of several computational modules for object and action recognition. It applies atten- tion mechanisms, visual learning and contextual as well as probabilistic reasoning to fuse individual results and verify their consistency. Database technologies are used for infor- mation storage and an XML based communication frame- work integrates all modules into a consistent architecture. |
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Keywords: | Robotics, Human-robot interaction |
Subjects: | H Engineering > H670 Robotics and Cybernetics |
Divisions: | College of Science > School of Computer Science |
ID Code: | 6946 |
Deposited On: | 23 Nov 2012 19:04 |
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