Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Machine Learning
Face Recognition Using Laplacianfaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Neighborhood Preserving Embedding
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Pixel Clustering by Using Complex Network Community Detection Technique
ISDA '07 Proceedings of the Seventh International Conference on Intelligent Systems Design and Applications
A complex network-based approach for boundary shape analysis
Pattern Recognition
Graph structure analysis based on complex network
Digital Signal Processing
Texture descriptor based on partially self-avoiding deterministic walker on networks
Expert Systems with Applications: An International Journal
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Face recognition is an important field that has received a lot of attention from computer vision community, with diverse set of applications in industry and science. This paper introduces a novel graph based method for face recognition which is rotation invariant. The main idea of the approach is to model the face image into a graph and use complex network methodology to extract a feature vector. We present the novel methodology and the experiments comparing it with four important and state of art algorithms. The results demonstrated that the proposed method has more positive results than the previous ones.