Face stimuli were created using FaceGen (Singular Inversions, Ontario, Canada): 200 images (400 × 400 pixels) represented faces (half males) of variable age, with hair, with a frontal view.
(b) Each set of samples with the same color represents face images under each viewpoint.
Several variants of LBP are available in literature to represent face images with compact feature sets.
(c) Each set of samples with the same color represents face images under each lighting condition.
We proposed to apply a 2DPCA to represent face by a few fractal features having a high discriminatory power.
In this paper, the 2D GHMs have been used to represent face images so that a face database may be compactly represented.
These results disclose that frontal parietal responses to "oddball" stimuli depicting enlarged faces (i.e. representing face fattening) are enhanced in successful dieters (karate athletes).
The fundamental objective of this step is dimensionality reduction by representing face space in lower dimensional space by generating features that are optimally uncorrelated.
Experimental results are provided to illustrate the performance of the proposed algorithms for facial feature detection and the accuracy of the designed scalable face model for representing face motion.
Here, a B-rep model is first transformed into a face adjacency graph (FAG), and then each node of an FAG is mapped to a point in a two-dimensional plane after representing face shape characteristics with two coordinates.
