DocumentCode :
1096484
Title :
Components and Their Topology for Robust Face Detection in the Presence of Partial Occlusions
Author :
Goldmann, Lutz ; Mönich, Ullrich J. ; Sikora, Thomas
Author_Institution :
Commun. Syst. Group, Tech. Univ. of Berlin, Berlin
Volume :
2
Issue :
3
fYear :
2007
Firstpage :
559
Lastpage :
569
Abstract :
This paper presents a novel approach for automatic and robust object detection. It utilizes a component-based approach that combines techniques from both statistical and structural pattern recognition domain. While the component detection relies on Haar-like features and an AdaBoost trained classifier cascade, the topology verification is based on graph matching techniques. The system was applied to face detection and the experiments show its outstanding performance in comparison to conventional face detection approaches. Especially in the presence of partial occlusions, uneven illumination, and out-of-plane rotations, it yields higher robustness. Furthermore, this paper provides a comprehensive review of recent approaches for object detection and gives an overview of available databases for face detection.
Keywords :
face recognition; graph theory; hidden feature removal; image matching; object detection; pattern classification; statistical analysis; AdaBoost trained classifier cascade; Haar-like features; component-based approach; graph matching; object detection; partial occlusions; robust face detection; statistical analysis; structural pattern recognition domain; Application software; Detectors; Face detection; Image databases; Lighting; Object detection; Pattern recognition; Robustness; Spatial databases; Topology; Boosting; Haar features; components; face detection; graph matching; topology;
fLanguage :
English
Journal_Title :
Information Forensics and Security, IEEE Transactions on
Publisher :
ieee
ISSN :
1556-6013
Type :
jour
DOI :
10.1109/TIFS.2007.902019
Filename :
4291543
Link To Document :
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