Automatic Facial Feature Detection and Location

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ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
Year:
1998

Citing 6
Cited 3

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Abstract

A method to automatically detect and locate human face features (eyes and mouth) in a 2D gray level image is presented. The method uses a genetic algorithm (CA) and an invariant description of the facial features to accomplish the task. The descriptors used are the well known first four translation, rotation and scale moment invariants proposed by Hu [6]. In a first step, an image possibly containing a face or a set of faces is first divided into small cells of fixed size. For each cell, the ordinary moments are next computed. Prom these quantities, the corresponding Hu's invariants are then derived. Human face feature detection and location is thus accomplished by grouping individual cells using a genetic algorithm by fitting a specific cost function. The cost function corresponds to the invariant description of a specified face feature (eye or mouth) given in terms of the corresponding gray level values.