Title :
Rotation invariant neural network-based face detection
Author :
Rowley, Henry A. ; Baluja, Shumeet ; Kanade, Takeo
Author_Institution :
Sch. of Comput. Sci., Carnegie Mellon Univ., Pittsburgh, PA, USA
Abstract :
In this paper, we present a neural network-based face detection system. Unlike similar systems which are limited to detecting upright, frontal faces, this system detects faces at any degree of rotation in the image plane. The system employs multiple networks; a “router” network first processes each input window to determine its orientation and then uses this information to prepare the window for one or more “detector” networks. We present the training methods for both types of networks. We also perform sensitivity analysis on the networks, and present empirical results on a large test set. Finally, we present preliminary results for detecting faces rotated out of the image plane, such as profiles and semi-profiles
Keywords :
face recognition; learning (artificial intelligence); neural nets; degree of rotation; face detection system; image plane; multiple networks; neural network-based; sensitivity analysis; test set; training methods; Change detection algorithms; Computer science; Data preprocessing; Detection algorithms; Detectors; Face detection; Histograms; Neural networks; Pixel; Skin;
Conference_Titel :
Computer Vision and Pattern Recognition, 1998. Proceedings. 1998 IEEE Computer Society Conference on
Conference_Location :
Santa Barbara, CA
Print_ISBN :
0-8186-8497-6
DOI :
10.1109/CVPR.1998.698585