FaceRecognition | Implement face recognition using PCA , LDA and LPP

FaceRecognition is a Java library. FaceRecognition has no bugs, it has no vulnerabilities and it has low support. However FaceRecognition build file is not available. You can download it from GitLab.

In this project, PCA, LDA and LPP are successfully implemented in Java for face recognition. After the system is trained by the training data, the feature space “eigenfaces” through PCA, the feature space “fisherfaces” through LDA and the feature space “laplacianfaces” through LPP are found using respective methods. Later in this report, W is used to represent the obtained feature space. Once W is obtained, training faces are projected to subspace defined by W to construct FaceDB. When an unknown face is needed to recognize, this test face is firstly projected onto subspace W. Afterward, the program finds the K nearest neighbors of the projected data in FaceDB. Finally, the class label is assigned to the test face according to the majority vote among the neighbors. This classification algorithm is known as K-nearest neighbor.