Paper Info
Title
Cascaded Face Detector with Multiple Templates
Abstract
This paper proposes a novel face detection algorithm which extracts a local image structure (LIS) feature and adopts a boosting approach to construct a cascaded face detector. Due to the locality of LIS, the extracted feature is not only robust to lighting variation but also is invariant to small degrees of rotation. With this robust property a multiple-template cascaded detection algorithm has been developed which can avoid rotating the image and also keep the ability to detect slanted faces. Because the multiple templates are constructed in the initialization stage, the proposed face detector can be executed very fast. Experiments on the BioID face database have shown the efficiency of this method.
Year
DOI
Venue
2007
10.1109/IIHMSP.2007.4457742
IIH-MSP
Keywords
Field
DocType
bioid face database,robust property,multiple templates,initialization stage,multiple-template cascaded detection algorithm,cascaded face detector,proposed face detector,novel face detection algorithm,local image structure,multiple template,slanted face,face recognition,feature extraction,face detection
Computer vision,Facial recognition system,Pattern recognition,Object-class detection,Three-dimensional face recognition,Computer science,Feature extraction,Artificial intelligence,Boosting (machine learning),Face detection,Initialization,Detector
Conference
ISBN
Citations 
PageRank 
0-7695-2994-1
0
0.34
References 
Authors
3
3
Name
Order
Citations
PageRank
Yea-shuan Huang147979.42
Hua-Ching Yan200.34
Ting-Chia Hsu322.05