3D face detection using transform invariant features

Date

2010-06-24

Author

AKAGÜNDÜZ, erdem
Ulusoy, İlkay

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A generic, transform invariant 3D facial feature detection method based on mean (H) and Gaussian (K) curvature analysis is proposed. A scale space of the HK values is constructed differently from the previous HK attempts. The 3D features are extracted from this scale space and used in a global topology, which is trained with a Gaussian model using only faces with neutral and frontal poses. The model is then tested against 1323 faces with various poses and expressions. The method is compared with four other representative algorithms from the previous literature for 3D facial feature localisation and face detection purposes.

URI

https://hdl.handle.net/11511/32917

Journal

ELECTRONICS LETTERS

DOI

https://doi.org/10.1049/el.2010.0132

Collections

Department of Electrical and Electronics Engineering, Article

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3D object representation using transform and scale invariant 3D features AKAGÜNDÜZ, Erdem; Ulusoy, İlkay (2007-10-21) An algorithm is proposed for 3D object representation using generic 3D features which are transformation and scale invariant. Descriptive 3D features and their relations are used to construct a graphical model for the object which is later trained and then used for detection purposes. Descriptive 3D features are the fundamental structures which are extracted from the surface of the 3D scanner output. This surface is described by mean and Gaussian curvature values at every data point at various scales and a ...
3D object recognition from range images using transform invariant object representation AKAGÜNDÜZ, erdem; Ulusoy, İlkay (Institution of Engineering and Technology (IET), 2010-10-28) 3D object recognition is performed using a scale and orientation invariant feature extraction method and a scale and orientation invariant topological representation. 3D surfaces are represented by sparse, repeatable, informative and semantically meaningful 3D surface structures, which are called multiscale features. These features are extracted with their scale (metric size and resolution) using the classified scale-space of 3D surface curvatures. Triplets of these features are used to represent the surfac...
3d face representation and recognition using spherical harmonics Tunçer, Fahri; Halıcı, Uğur; Department of Electrical and Electronics Engineering (2008) In this study, a 3D face representation and recognition method based on spherical harmonics expansion is proposed. The input data to the method is range image of the face. This data is called 2.5 dimensional. Input faces are manually marked on the two eyes, nose and chin points. In two dimensions, using the marker points, the human face is modeled as two concentric half ellipses for the selection of region of interest. These marker points are also used in three dimensions to register the faces so that the n...
3D Object Recognition by Geometric Hashing Eskizara, Omer; Akagündüz, Erdem; Ulusoy, İlkay (2009-01-01) Using transform invariant 3D fatures obtained from a database of 3D range images, geometric hashing is applied for the purpose of 3D object recognition. Mean (H) and Gaussian (K) curvature values within a scale-space of the surface is used Since H and K values are used and a scale-space of the surface is constructed the method is independent of transformation and resolution. The method is tested on the Stuttgart 3D range image database [1].
3D object recognition using scale space of curvatures Akagündüz, Erdem; Ulusoy, İlkay; Department of Electrical and Electronics Engineering (2011) In this thesis, a generic, scale and resolution invariant method to extract 3D features from 3D surfaces, is proposed. Features are extracted with their scale (metric size and resolution) from range images using scale-space of 3D surface curvatures. Different from previous scale-space approaches; connected components within the classified curvature scale-space are extracted as features. Furthermore, scales of features are extracted invariant of the metric size or the sampling of the range images. Geometric ...

Citation Formats

e. AKAGÜNDÜZ and İ. Ulusoy, “3D face detection using transform invariant features,” ELECTRONICS LETTERS, pp. 905–906, 2010, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/32917.