SPHERICAL HARMONICAL FEATURES FOR 3D-FACE USING KNN AND SVM CLASSIFIER

    In this design Shape-based, Spherical Harmonic Features (SHF) for 3-D FR developed using Matlab with Verilog HDL. This SHFs capture both gross shape and fine surface details of facial surfaces through the energies contained in spherical harmonics at different frequencies. They are computed on a canonical facial representation, namely Spherical Depth Map (SDM). Because the predictive contribution of each feature in SHF is different, especially in the presence of facial expressions and possible partial occlusions. To evaluate the effectiveness of KNN and SVM classifier was conducted on the selected feature set by incrementally increasing the number of features used on the test set until the full list of features was reached. 

Reference Paper: Learning the Spherical Harmonic Features for 3-D Face Recognition
Author’s Name: Peijiang Liu, Yunhong Wang, and, Di Huang
Source: IEEE
Year:2013
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SIMULATION VIDEO DEMO                                                                                                 



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