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Scale-Space Volume Descriptors for Automatic 3D Facial Feature Extraction

Authors: Daniel Chen, George Mamic, Clinton Fookes, Sridha Sridharan


An automatic method for the extraction of feature points for face based applications is proposed. The system is based upon volumetric feature descriptors, which in this paper has been extended to incorporate scale space. The method is robust to noise and has the ability to extract local and holistic features simultaneously from faces stored in a database. Extracted features are stable over a range of faces, with results indicating that in terms of intra-ID variability, the technique has the ability to outperform manual landmarking.

Keywords: Feature Extraction, Scale space volume descriptor

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