Title :
A novel neural network technique for the detection of human faces in visual scenes
Author :
Sarris, Nikos ; Grammalidis, Nikos ; Strintzis, Michael G.
Author_Institution :
Electr. & Comput. Eng. Dept., Aristotelian Univ. of Thessaloniki, Greece
Abstract :
This paper presents a user interactive system that manages, with minimum user interaction, to locate a set of characteristic feature points in the frontal view of a person´s face. Our method is user adaptive and is implemented as a combination of a classification-based facial region extraction technique with a transition based facial feature extraction method. First, we allow the system to be trained to recognize image blocks belonging to the facial area by proper training of a feedforward neural network. Then, we initialize the feature detection algorithm with a blink of the user´s eyes, which localizes the exact contours of the eyes. Finally, we locate the remaining facial features (face contour, eyebrows, mouth and nose) by adaptively thresholding the facial area and utilizing knowledge of the geometrical structure of the face
Keywords :
edge detection; face recognition; feature extraction; feedforward neural nets; interactive systems; learning (artificial intelligence); pattern classification; user interfaces; contour detection; feature extraction; feedforward neural network; human face recognition; image blocks; interactive system; pattern classification; user interface; Computer vision; Eyes; Face detection; Face recognition; Facial features; Feedforward neural networks; Humans; Image recognition; Interactive systems; Neural networks;
Conference_Titel :
Neural Network Applications in Electrical Engineering, 2000. NEUREL 2000. Proceedings of the 5th Seminar on
Conference_Location :
Belgrade
Print_ISBN :
0-7803-5512-1
DOI :
10.1109/NEUREL.2000.902391