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Author Samir ♦ Bandyopadhyay, K.
Source CiteSeerX
Content type Text
File Format PDF
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Face Segmentation ♦ Facial Feature Extraction ♦ Grey Level Image ♦ Face Recognition ♦ Video Coding ♦ Oriented Template Correlation ♦ Matching Stage ♦ Algorithm Therefore ♦ Automatic Localization ♦ Multi-modal Human Machine Interface ♦ Edge Information ♦ Current Image Position ♦ Frontal Head ♦ Shoulder View ♦ Visual Scene ♦ Abstract-an Important Topic ♦ Shoulder Region ♦ Large Database ♦ Detection Capability
Abstract Abstract-An important topic in face recognition as well as in video coding or multi-modal human machine interfaces is the automatic localization of faces or head and- shoulder regions in visual scenes. The algorithms therefore should be computationally efficient and robust against distortions like varying lighting conditions. This paper describes a method for segmenting frontal head and shoulder views of persons from grey level images. The segmentation is done by oriented template correlation. This matching method only depends on edge information, especially the orientation of the edges. In the matching stage we calculate the possibility for a face at the current image position using this model. The detection capabilities of the presented algorithm are evaluated on a large database of 1004 images each containing one or more faces.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article