DocumentCode :
2491233
Title :
Automatic extraction of face contours
Author :
Hsu, Chih-Yu ; Wang, Hao-Feng ; Wang, Hui-Ching ; Tseng, Kuo-Kun ; Tang, Yih-Jing
Author_Institution :
Dept. of Appl. Math., Nat. Chung-Hsing Univ., Taichung, Taiwan
fYear :
2010
fDate :
18-23 July 2010
Firstpage :
1
Lastpage :
8
Abstract :
Accuracy of the human face contour can help evaluate the facial orientation to retrieve facial features to identifying or verifying a human facial expression. Automatic extraction human face contour algorithm with high accuracy is necessary. In this paper, a novel flowchart of the face contour extraction algorithm was proposed for improving accuracy of face contours. Poisson Gradient Vector Flow (PGVF) Active Contour Model with an edge map is used to extract face contours. The edge map of a whole face contour is constructed by the Divided-and-Conquer technique and Canny edge detector. Genetic algorithm is implemented to automatically find the parameters of Canny edge detector. Three datasets with images and temporal sequence images have been tested for evaluation of the proposed algorithm. The expermental results demonstrated the algorithm can obtain accurate face contours
Keywords :
divide and conquer methods; edge detection; face recognition; feature extraction; flowcharting; image retrieval; image sequences; stochastic processes; Canny edge detector; PGVF; Poisson gradient vector flow; active contour model; automatic extraction human face contour algorithm; divided-and-conquer technique; edge map; facial orientation; flowchart; genetic algorithm; temporal sequence images; Active contours; Biomedical imaging; Detectors; Face; Humans; Image edge detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks (IJCNN), The 2010 International Joint Conference on
Conference_Location :
Barcelona
ISSN :
1098-7576
Print_ISBN :
978-1-4244-6916-1
Type :
conf
DOI :
10.1109/IJCNN.2010.5596587
Filename :
5596587
Link To Document :
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