{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/72839"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/72839","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Face recognition using hidden Markov model supervectors","abstract":"This project attempts to boost the results of face recognition algorithms already established to perform face recognition by augmenting the architecture and using HMM-based supervector classification. In this thesis, the work of Tang’s 2010 dissertation is used such that the HMM based classifier takes on a UBM-MAP adaptation based approach. In addition, Tang’s work is extended to the case of pseudo 2-dimensional HMMs. Thus, a supervector classifier for pseudo 2DHMMs is developed and then applied to the task of face recognition. 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