DocumentCode :
1798766
Title :
A novel efficient method for abnormal face detection in ATM
Author :
Xihao Zhang ; Lin Zhou ; Tao Zhang ; Jie Yang
Author_Institution :
Dept. of Electron. Eng., Shanghai Jiao Tong Univ., Shanghai, China
fYear :
2014
fDate :
7-9 July 2014
Firstpage :
695
Lastpage :
700
Abstract :
Face detection in video is a challenging and interesting topic, especially when it´s applied in Automatic Teller Machine (ATM). We propose an efficient algorithm to detect arbitrary occluded faces in ATM surveillance. A novel and time-saving foreground extraction method is proposed to obtain accurate foreground. After that, we locate the face with two cascaded steps. An empirical rule-based face localization is utilized to locate the face roughly, then adaptive ellipse fitting helps accurately locate the face. In order to detect the occluded faces, we use ADABOOST to combine a skin color detection and face templates matching. Experimental results show that our algorithm achieve a high detection rate while keep the false negative rate pretty low.
Keywords :
automatic teller machines; curve fitting; face recognition; feature extraction; image colour analysis; image matching; learning (artificial intelligence); object detection; video signal processing; video surveillance; ATM surveillance; AdaBoost; abnormal face detection; automatic teller machine; ellipse fitting; face templates matching; occluded faces; rule-based face localization; skin color detection; time-saving foreground extraction; video; Color; Face; Face detection; Image color analysis; Skin; Surveillance; Training;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Audio, Language and Image Processing (ICALIP), 2014 International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4799-3902-2
Type :
conf
DOI :
10.1109/ICALIP.2014.7009884
Filename :
7009884
Link To Document :
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