Please use this identifier to cite or link to this item: https://doi.org/10.1109/34.655648
Title: Example-based learning for view-based human face detection
Authors: Sung, K.-K. 
Poggio, T.
Keywords: Density estimation
Example selection
Example-based learning
Face detection
Gaussian mixture model
Object detection
Pattern recognition
View-based recognition
Issue Date: 1998
Citation: Sung, K.-K., Poggio, T. (1998). Example-based learning for view-based human face detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 20 (1) : 39-51. ScholarBank@NUS Repository. https://doi.org/10.1109/34.655648
Abstract: We present an example-based learning approach for locating vertical frontal views of human faces in complex scenes. The technique models the distribution of human face patterns by means of a few view-based "face" and "nonface" model clusters. At each image location, a difference feature vector is computed between the local image pattern and the distribution-based model. A trained classifier determines, based on the difference feature vector measurements, whether or not a human face exists at the current image location. We show empirically that the distance metric we adopt for computing difference feature vectors, and the "nonface" clusters we include in our distribution-based model, are both critical for the success of our system. ©1998 IEEE.
Source Title: IEEE Transactions on Pattern Analysis and Machine Intelligence
URI: http://scholarbank.nus.edu.sg/handle/10635/99274
ISSN: 01628828
DOI: 10.1109/34.655648
Appears in Collections:Staff Publications

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