Example-based learning for view-based human face detection

Example-based learning for view-based human face detection (1998)

by Kah-kay Sung , Tomaso Poggio

Venue:	IEEE Transactions on Pattern Analysis and Machine Intelligence
Citations:	505 - 18 self

Datum	Value	Source
TITLE	Example-based learning for view-based human face detection	INFERENCE
AUTHOR NAME	Kah-kay Sung	SVM HeaderParse 0.2
AUTHOR NAME	Tomaso Poggio	SVM HeaderParse 0.2
ABSTRACT	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. Index Terms—Face detection, object detection, example-based learning, example selection, pattern recognition, view-based	SVM HeaderParse 0.2
YEAR	1998	INFERENCE
VENUE	IEEE Transactions on Pattern Analysis and Machine Intelligence	INFERENCE
VENUE TYPE	JOURNAL	INFERENCE
PAGES	39--51	INFERENCE
VOLUME	20	INFERENCE
CITATIONS	1 found	ParsCit 1.0