FACE EXPRESSION IDENTIFICATION USING IMAGE FEATURE CLUSTRING AND QUERY SCHEME
Web mining techniques are used to analyze the web page contents and usage details. Human facial images are shared in the internet and tagged with additional information. Auto face annotation techniques are used to annotate facial images automatically. Annotations are used in online photo search and management. Classification techniques are used to assign the facial annotation. Supervised or semi-supervised machine learning techniques are used to train the classification models. Facial images with labels are used in the training process. Noisy and incomplete labels are referred as weak labels. Search-based face annotation (SBFA) is assigned by mining weakly labeled facial images available on the World Wide Web (WWW). Unsupervised label refinement (ULR) approach is used for refining the labels of web facial images with machine learning techniques. ULR scheme is used to enhance the label quality using graph-based and low-rank learning approach. The training phase is designed with facial image collection, facial feature extraction, feature indexing and label refinement learning steps. Similar face retrieval and voting based face annotation tasks are carried out under the testing phase. Clustering-Based Approximation (CBA) algorithm is applied to improve the scalability. Bisecting K-means clustering based algorithm (BCBA) and divisive clustering based algorithm (DCBA) are used to group up the facial images. Multi step Gradient Algorithm is used for label refinement process. The web face annotation scheme is enhanced to improve the label quality with low refinement overhead. Noise reduction is method is integrated with the label refinement process. Duplicate name removal process is integrated with the system. The indexing scheme is enhanced with weight values for the labels. Social contextual information is used to manage the query facial image relevancy issues. KeywordsAuto Face Annotation ,Query Facial Image , K-Means Clustering, Noise Reduction, Weakly Labeled Facial Images