Attribute and Identity Based Face Image Retrieval

Large-scale content-based face image retrieval is an enabling technology for many emerging applications. The existing system presents a novel approach to face recognition which considers both shape and texture information and attribute information to represent face images. Existing system contain semantic cues of the face photos to improve content- based face image retrieval by constructing semantic codewords for efficient large- scale face retrieval. Here, I propose to combine identity based face image retrieval with the existing system. Proposed system contains CBIR concepts like indexing, clustering, searching (attribute searching and identity based searching) and face image retrieval. Most of the systems related to existing system are suffering from low recall problems. One solution for this problem is to construct semantic codewords by using extra textual information. So I propose the identity based face image retrieval concept.