Context-Aware Local Binary Feature Learning : An Approach For Face Recognition - Ahire, Sushmitamai K; Wankhade, Nilesh R (International Journal of Computer Sciences and Engineering, 2019)
This system uses Context-Aware Local Binary Feature Learning (CA-LBFL) Method for face recognition. Learning based methods such as DFD and CBFD learn features representation from raw pixel and they are more susceptible to noise where existing local feature descriptors are hand crafted and they require strong prior knowledge and heuristic. Proposed system uses contextual information for face recognition because context provides strong prior knowledge. It helps to enhance the robustness and stableness of various visual analysis tasks. to jointly learn multiple projections matrices for mapping we make use of context-aware local binary multi-scale feature learning (CA-LBMFL), where each projection matrix corresponds to a specific scale of pixel difference vector (PDV). PDVs are extracted from image and stored in a text file in the binary form. Face recognition is performed on the basis of this extracted features. For heterogeneous face matching we implement coupled learning methods based on CA-LBFL and CA-LBMFL. Experimental result is based on two widely used datasets LWF and YTF.