Abstract
We describe the challenge of combining continuous computer vision techniques and qualitative, symbolic methods to achieve a system capable of cognitive vision. Key to a truly cognitive system, is the ability to learn: to be able to build and use models constructed autonomously from sensory input. In this paper we overview a number of steps we have taken along the route to the construction of such a system, and discuss some remaining challenges. © Springer-Verlag Berlin Heidelberg 2006.
| Original language | English |
|---|---|
| Title of host publication | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci. |
| Publisher | Springer Nature |
| Pages | 221-246 |
| Number of pages | 25 |
| Volume | 3948 |
| ISBN (Print) | 9783540339717 |
| DOIs | |
| Publication status | Published - 2006 |
| Event | Cognitive Vision Systems, Sampling the Spectrum of Approaches [based on a Dagstuhl seminar] - Duration: 1 Jan 1824 → … http://dblp.uni-trier.de/db/conf/dagstuhl/vision2006.html#CohnHBDGMNS06http://dblp.uni-trier.de/rec/bibtex/conf/dagstuhl/CohnHBDGMNS06.xmlhttp://dblp.uni-trier.de/rec/bibtex/conf/dagstuhl/CohnHBDGMNS06 |
Publication series
| Name | Lecture Notes in Computer Science |
|---|
Conference
| Conference | Cognitive Vision Systems, Sampling the Spectrum of Approaches [based on a Dagstuhl seminar] |
|---|---|
| Period | 1/01/24 → … |
| Internet address |
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