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Published June 1995 | Published
Book Section - Chapter Open

Finding Faces in Cluttered Scenes using Random Labeled Graph Matching

Abstract

An algorithm for locating quasi-frontal views of human faces in cluttered scenes is presented. The algorithm works by coupling a set of local feature detectors with a statistical model of the mutual distances between facial features it is invariant with respect to translation, rotation (in the plane), and scale and can handle partial occlusions of the face. On a challenging database with complicated and varied backgrounds, the algorithm achieved a correct localization rate of 95% in images where the face appeared quasi-frontally.

Additional Information

© 1995 IEEE. Date of Current Version: 06 August 2002. This work was supported by the Center for Neuromorphic Systems Engineering as a part of the National Science Foundation (NSF) Engineering Research Center Program, and by the California Trade and Commerce Agency, Office of Strategic Technology. Additional funding was provided by ONR grant n. N00014-93-1-0990, an NSF National Young Investigator award, a grant from Intel, and a grant from Caltech. We are also very grateful to Jitendra Malik for useful discussions.

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