Viewpoint generalization in face recognition: The role of category-speci c processes

The statistical structure of a class of objects such as human faces can be exploited to recognize familiar faces from novel viewpoints and under variable illumination conditions. We present computational and psychophysical data concerning the extent to which class-based learning transfers or generalizes within the class of faces. We rst examine the computational prerequisite for generalization across views of novel faces, namely, the similarity of di erent faces to each other. We next describe two computational models which exploit the similarity structure of the class of faces. The performance of these models constrains hypotheses about the nature of face representation in human vision, and supports the notion that human face processing operates in a class-based fashion. Finally, we relate the computational data to well-established ndings in the human memory literature concerning the relationship between the typicality and recognizability of faces.
Keywords No keywords specified (fix it)
Categories (categorize this paper)
 Save to my reading list
Follow the author(s)
My bibliography
Export citation
Find it on Scholar
Edit this record
Mark as duplicate
Revision history Request removal from index Translate to english
Download options
PhilPapers Archive

Upload a copy of this paper     Check publisher's policy on self-archival     Papers currently archived: 21,395
External links
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
Through your library
References found in this work BETA

No references found.

Add more references

Citations of this work BETA

No citations found.

Add more citations

Similar books and articles

Monthly downloads

Added to index


Total downloads

22 ( #178,006 of 1,911,401 )

Recent downloads (6 months)

4 ( #177,396 of 1,911,401 )

How can I increase my downloads?

My notes
Sign in to use this feature

Start a new thread
There  are no threads in this forum
Nothing in this forum yet.