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Components and Their Topology for Robust Face Detection in the Presence of Partial Occlusions
Citation key 1102Goldmann2007
Author Lutz Goldmann and Ullrich J. Mönich and Thomas Sikora
Pages 559–569
Year 2007
DOI 10.1109/TIFS.2007.902019
Journal IEEE Transactions on Information Forensics and Security, Special Issue on Human Detection and Recognition
Volume 2
Number 3/2
Month sep
Note ISSN: 1556-6013
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.
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