MIT Libraries logoDSpace@MIT

MIT
View Item 
  • DSpace@MIT Home
  • Computer Science and Artificial Intelligence Lab (CSAIL)
  • Artificial Intelligence Lab Publications
  • AI Memos (1959 - 2004)
  • View Item
  • DSpace@MIT Home
  • Computer Science and Artificial Intelligence Lab (CSAIL)
  • Artificial Intelligence Lab Publications
  • AI Memos (1959 - 2004)
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

An Empirical Comparison of SNoW and SVMs for Face Detection

Author(s)
Alvira, Mariano; Rifkin, Ryan
Thumbnail
DownloadAIM-2001-004.ps (1.175Mb)
Additional downloads
AIM-2001-004.pdf (311.6Kb)
Metadata
Show full item record
Abstract
Impressive claims have been made for the performance of the SNoW algorithm on face detection tasks by Yang et. al. [7]. In particular, by looking at both their results and those of Heisele et. al. [3], one could infer that the SNoW system performed substantially better than an SVM-based system, even when the SVM used a polynomial kernel and the SNoW system used a particularly simplistic 'primitive' linear representation. We evaluated the two approaches in a controlled experiment, looking directly at performance on a simple, fixed-sized test set, isolating out 'infrastructure' issues related to detecting faces at various scales in large images. We found that SNoW performed about as well as linear SVMs, and substantially worse than polynomial SVMs.
Date issued
2001-01-01
URI
http://hdl.handle.net/1721.1/7219
Other identifiers
AIM-2001-004
CBCL-193
Series/Report no.
AIM-2001-004CBCL-193

Collections
  • AI Memos (1959 - 2004)
  • CBCL Memos (1993 - 2004)

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

Login

Statistics

OA StatisticsStatistics by CountryStatistics by Department
MIT Libraries
PrivacyPermissionsAccessibilityContact us
MIT
Content created by the MIT Libraries, CC BY-NC unless otherwise noted. Notify us about copyright concerns.