Fast object detection with occlusions

YY Lin*, TL Liu, Chiou Shann Fuh

*Corresponding author for this work

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

28 Scopus citations

Abstract

We describe a new framework, based on boosting algorithms and cascade structures, to efficiently detect objects/faces with occlusions. While our approach is motivated by the work of Viola and Jones, several techniques have been developed for establishing a more general system, including (i) a robust boosting scheme, to select useful weak learners and to avoid overfitting; (ii) reinforcement training, to reduce false-positive rates via a more effective training procedure for boosted cascades; and (iii) cascading with evidence, to extend the system to handle occlusions, without compromising in detection speed. Experimental results on detecting faces under various situations are provided to demonstrate the performances of the proposed method.

Original languageEnglish
Title of host publicationCOMPUTER VISION - ECCV 2004, PT 1
EditorsT Pajdla, J Matas
PublisherSpringer-Verlag Berlin Heidelberg
Pages402-413
Number of pages12
ISBN (Print)3-540-21984-6
DOIs
StatePublished - 2004
Event8th European Conference on Computer Vision - Prague, Czech Republic
Duration: 11 May 200414 May 2004

Publication series

NameLecture Notes in Computer Science
PublisherSPRINGER-VERLAG BERLIN
Volume3021
ISSN (Print)0302-9743

Conference

Conference8th European Conference on Computer Vision
CountryCzech Republic
CityPrague
Period11/05/0414/05/04

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