2026-09-23T18:10:06Zhttps://api.repository.cam.ac.uk/server/oai/request

oai:www.repository.cam.ac.uk:1810/2448712024-06-26T13:39:27Zcom_1810_213729com_1810_256065col_1810_219485

Face recognition using Hidden Markov Models 10.17863/CAM.14051 Samaria, Ferdinando Silvestro This dissertation introduces work on face recognition using a novel technique based on Hidden Markov Models (HMMs). Through the integration of a priori structural knowledge with statistical information, HMMs can be used successfully to encode face features. The results reported are obtained using a database of images of 40 subjects, with 5 training images and 5 test images for each. It is shown how standard one-dimensional HMMs in the shape of top-bottom models can be parameterised, yielding successful recognition rates of up to around 85%. The insights gained from top-bottom models are extended to pseudo two-dimensional HMMs, which offer a better and more flexible model, that describes some of the twodimensional dependencies missed by the standard one-dimensional model. It is shown how pseudo two-dimensional HMMs can be implemented, yielding successful recognition rates of up to around 95%. The performance of the HMMs is compared with the Eigenface approach and various domain and resolution experiments are also carried out. Finally, the performance of the HMM is evaluated in a fully automated system, where database images are cropped automatically. University of Cambridge 1995-02-14 Thesis Doctoral Doctor of Philosophy (PhD) en https://www.repository.cam.ac.uk/handle/1810/244871 https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/b185ad0f-ee2a-4cbe-8fe7-60af62cef13a/download eba5e6d2be8c5fe298bb734a2c23325f https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/a16532e7-a566-4658-9705-ab6e3773a5ef/download 835269bda140c10400fe0606a14c3d21 https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/6be414db-3776-4189-8122-45efa89702e8/download 1cf06fcf0e0e168cb888c748ca1884cf https://www.rioxx.net/licenses/all-rights-reserved/ This work was supported by a Trinity College Internal Graduate Studentship and an Olivetti Research Ltd, CASE award. Face recognition Face segmentation automatic feature extraction Hidden Markov Models stochastic modelling