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Incremental subclass discriminant analysis : a case study in face recognition
Content Provider | Indraprastha Institute of Information Technology, Delhi |
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Author | Lamba, Hemank Dhamecha, Tejas I Vatsa, Mayank Singh, Richa |
Abstract | Subclass discriminant analysis is found to be applicable under various scenarios. However, it is computationally very expensive to update the between-class and within-class scatter matrices. This research presents an incremental subclass discriminant analysis algorithm to update SDA in incremental manner with increasing number of samples per class. The effectiveness of the proposed algorithm is demonstrated using face recognition in terms of identification accuracy and training time. Experiments are performed on the AR face database and compared with other subspace based incremental and batch learning algorithms. The results illustrate that Incremental SDA yields significant reduction in time compared to SDA along with improving the accuracy compared to other incremental approaches. |
File Format | |
Language | English |
Access Restriction | Open |
Subject Keyword | Incremental SDA Subclass Face Recognition Face Identification |
Content Type | Text |
Resource Type | Technical Report |
Subject | Data processing & computer science |