Title :
Multi-feature Fusion Method of Driver Face Location 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
Abstract :
Speedy and reliable face location is a key for monitoring driver fatigue driving condition using machine vision methods. According to the disadvantage of face location methods based on single feature in accuracy and reliability at present, first, an improved face location method based on Haar-like feature and Adaboost is used to detect the possibly existing face region in the whole image, then the detected region is extended properly and a face location method based on skin color feature in normalized rgb and HSV color spaces is used to locate the face again in the extended area, finally, fusion location of driver face region is achieved by the defined area coincidence degree and prior knowledge of human face. Experiments carried out in various road environments demonstrate the validity of the fusion method proposed.
Keywords :
Haar transforms; driver information systems; face recognition; feature extraction; image colour analysis; image fusion; object detection; Adaboost; Haar-like feature; area coincidence degree; driver face location; driver fatigue; driving condition; face region detection; machine vision; multifeature fusion; skin color feature; Circuits; Face detection; Fatigue; Flowcharts; Humans; Injuries; Life estimation; Skin; State estimation; US Department of Transportation; Haar-like feature; area coincidence degree; face location; prior knowledge; skin color feature;
Conference_Titel :
Circuits, Communications and Systems, 2009. PACCS '09. Pacific-Asia Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-0-7695-3614-9
DOI :
10.1109/PACCS.2009.49