Published 2007
| Submitted
Journal Article
Open
Attention in hierarchical models of object recognition
- Creators
- Walther, Dirk B.
-
Koch, Christof
Chicago
Abstract
Object recognition and visual attention are tightly linked processes in human perception. Over the last three decades, many models have been suggested to explain these two processes and their interactions, and in some cases these models appear to contradict each other. We suggest a unifying framework for object recognition and attention and review the existing modeling literature in this context. Furthermore, we demonstrate a proof-of-concept implementation for sharing complex features between recognition and attention as a mode of top-down attention to particular objects or object categories.
Additional Information
Copyright © 2007 Elsevier. Thomas Serre and Tomaso Poggio collaborated on parts of the work on sharing features between object detection and top-down attention. We would like to thank Karen F. Bernhardt-Walther, Kerstin Preuschoff, and Daniel Simons for helpful discussions and feedback on versions of the manuscript. This work was funded by DARPA, the NSF, the NIH, the NIMH, the ONR, the Keck Foundation, and a Beckman Postdoctoral Fellowship to D.B.W.Attached Files
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Additional details
- Eprint ID
- 40618
- DOI
- 10.1016/S0079-6123(06)65005-X
- Resolver ID
- CaltechAUTHORS:20130816-103304790
- DARPA
- NSF
- NIH
- NIMH
- U.S. Office of Naval Research
- Keck Foundation
- Beckman Postdoctoral Fellowship
- Created
-
2008-01-16Created from EPrint's datestamp field
- Updated
-
2021-11-10Created from EPrint's last_modified field
- Caltech groups
- Koch Laboratory (KLAB)