Learning a rare event detection cascade by direct feature selection

Jianxin Wu, James M. Rehg, Matthew D. Mullin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Face detection is a canonical example of a rare event detection problem, in which target patterns occur with much lower frequency than nontargets. Out of millions of face-sized windows in an input image, for example, only a few will typically contain a face. Viola and Jones recently proposed a cascade architecture for face detection which successfully addresses the rare event nature of the task. A central part of their method is a feature selection algorithm based on AdaBoost. We present a novel cascade learning algorithm based on forward feature selection which is two orders of magnitude faster than the Viola-Jones approach and yields classifiers of equivalent quality. This faster method could be used for more demanding classification tasks, such as on-line learning.

Original languageEnglish (US)
Title of host publicationAdvances in Neural Information Processing Systems 16 - Proceedings of the 2003 Conference, NIPS 2003
PublisherNeural information processing systems foundation
ISBN (Print)0262201526, 9780262201520
StatePublished - 2004
Externally publishedYes
Event17th Annual Conference on Neural Information Processing Systems, NIPS 2003 - Vancouver, BC, Canada
Duration: Dec 8 2003Dec 13 2003

Publication series

NameAdvances in Neural Information Processing Systems
ISSN (Print)1049-5258

Other

Other17th Annual Conference on Neural Information Processing Systems, NIPS 2003
Country/TerritoryCanada
CityVancouver, BC
Period12/8/0312/13/03

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Signal Processing

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