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.<>
Finding faces in cluttered scenes using random labeled graph matching
1995-01-01
921259 byte
Conference paper
Electronic Resource
English
Finding Faces in Cluttered Scenes Using Labeled Random Graph Matching
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