Name
Abstract | ||
|---|---|---|
The emerging cognitive vision paradigm is concerned with vision systems that evaluate, gather and integrate contextual 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 research on cognitive computer vision. In this contribution, we present a system that consists of several computational modules for object and action recognition. It applies attention mechanisms, visual learning and contextual as well as probabilistic reasoning to fuse individual results and verify their consistency. Database technologies are used for information storage and an XML based communication framework integrates all modules into a consistent architecture. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1109/CVPR.2004.1315250 | CVPR |
Keywords | Field | DocType |
XML,cognitive systems,computer vision,database management systems,gesture recognition,inference mechanisms,information storage,learning systems,XML based communication framework,action recognition,attention mechanisms,cognitive computer vision,cognitive vision system,database technologies,information storage,integrate contextual knowledge,office environments,probabilistic reasoning,visual analysis,visual learning | Cognitive computer,Computer vision,Architecture,XML,Computer science,Gesture recognition,Testbed,Artificial intelligence,Visual learning,Probabilistic logic,Machine learning,Vision science | Conference |
Volume | ISSN | Citations |
2 | 1063-6919 | 14 |
PageRank | References | Authors |
0.97 | 16 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Christian Bauckhage | 1 | 1979 | 195.86 |
| M. Hanheide | 2 | 65 | 4.83 |
| S. Wrede | 3 | 33 | 3.70 |
| Gerhard Sagerer | 4 | 300 | 38.77 |