Face Image Retrieval using Sparse Code and Age Group Estimation by using Face Angle

Rise of many social Medias have led to an increase in the consumer photos available which are highly manipulative. Large scale content based face image retrieval is an enabling technology for many emerging applications including automatic face annotation, crime investigation etc. In this system retrieve the similar face images of query image from data base and also do the approximate age group estimation. In content based face recognition system facial appearance and features of data base image changes as the age progress and data base should be updated which is a tedious task. So age group estimation is an important task and it is done by face angle calculation. High level human attributes like rice, gender etc are detected. Weber-s Local Descriptor (WLD) is used for gender recognition. Local Binary pattern (LBP) is used to detect the rice. A method namely sparse coding is used to generate distinct code for each face. The effectiveness of different attributes and vital factors essential for face retrieval is mainly investigated.