Facial Expression Recognition based on PCA Feature Extraction and Distancebased Hashing K-nearest Neighbor Classification
Jian He · Intelligent Computer and Applications · 2012
The paper uses dimensionality reduction which is based on principal component analysis(PCA)to extract facial expression features,and combines an K-nearest neighbor classification algorithm based on distance-based hashing to recognize facial expressions.First,the paper uses Haar-like feature and AdaBoost algorithm to detect human face and preprocess the face image;then uses PCA to extract facial expression feature and insert it to hash table;finally adopts K-nearest neighbor classification algorithm to recognize facial expression.After reconstructing the feature library to hash tables,the recognition efficiency has been enhanced largely.