DocumentCode :
2330534
Title :
Multi-feature driver face detection based on area coincidence degree and prior knowledge
Author :
Sun, Wei ; Zhang, Weigong ; Zhang, Xiaorui ; Chen, Gang ; Lv, Chengxu
Author_Institution :
Dept. of Instrum. Sci. & Eng., Southeast Univ., Nanjing, China
fYear :
2009
fDate :
25-27 May 2009
Firstpage :
222
Lastpage :
225
Abstract :
Exact and fast driver face detection is a key for recognising whether drivers are fatigue or not by detecting ficial organs while driving using machine vision technology. Aiming at the limitation of driver face detection algorithm based on single feature in detection precision and reliability, a novel fusion algorithm of driver face detection is proposed. Firstly, an improved face detection algorithm based on Haar-like feature is used to detect the possibly existing initial face region in the whole image, then the initial face region detected is extended properly and a face detection algorithm based on skin color feature in rgb space is used to locate the face region again in the extended area, finally, fusion detection of driver face region is achieved by the defined area coincidence degree and geometric prior knowledge of human face. Experiments carried out in various complicated road environments show the algorithm proposed is of strong robustness on lighting changes, driver head rotation, and having glasses, etc., while at detection precision and reliability, it offers a noticeable enhancement compared with the single feature based algorithms.
Keywords :
Haar transforms; computer vision; face recognition; image colour analysis; road safety; sensor fusion; Haar-like feature; area coincidence degree; detection precision; detection reliability; ficial organs detection; fusion detection; initial face region detection; machine vision technology; multifeature driver face detection; prior knowledge; skin color feature; Computer vision; Face detection; Face recognition; Fatigue; Head; Humans; Machine vision; Roads; Robustness; Skin; area coincidence degree; face detection; fatigue driving; multi-feature fusion; prior knowledge;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics and Applications, 2009. ICIEA 2009. 4th IEEE Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4244-2799-4
Electronic_ISBN :
978-1-4244-2800-7
Type :
conf
DOI :
10.1109/ICIEA.2009.5138200
Filename :
5138200
Link To Document :
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