Matches in SemOpenAlex for { <https://semopenalex.org/work/W2020897165> ?p ?o ?g. }
Showing items 1 to 83 of
83
with 100 items per page.
- W2020897165 abstract "We propose a model for extracting facial features robustly for face recognition under large pose variations in videos. The facial features are retrieved via Gabor Wavelet Transform with an embedded Hidden Markov Model (HMM), which decodes each observed face image into a state sequence. While an HMM can segment images into features at a fixed pose, multiple HMMs are trained for each individual to extract features robustly under large pose variation. The effectiveness of the proposed approach is validated through using the Sheffield Face Database. Our experiment shows better result than several other methods such as DCT+HMM,DWT+HMM, etc." @default.
- W2020897165 created "2016-06-24" @default.
- W2020897165 creator A5014486696 @default.
- W2020897165 creator A5074890965 @default.
- W2020897165 date "2010-10-01" @default.
- W2020897165 modified "2023-09-23" @default.
- W2020897165 title "An HMM-Based Face Recognition Model under Variable Pose in Videos" @default.
- W2020897165 cites W1480865305 @default.
- W2020897165 cites W1967475838 @default.
- W2020897165 cites W1989702938 @default.
- W2020897165 cites W2051439328 @default.
- W2020897165 cites W2057832152 @default.
- W2020897165 cites W2106905947 @default.
- W2020897165 cites W2134071121 @default.
- W2020897165 cites W2138584058 @default.
- W2020897165 cites W2140836279 @default.
- W2020897165 cites W2141425367 @default.
- W2020897165 cites W2148601301 @default.
- W2020897165 cites W2164598857 @default.
- W2020897165 cites W2165731615 @default.
- W2020897165 cites W2351876761 @default.
- W2020897165 doi "https://doi.org/10.1109/ccpr.2010.5659144" @default.
- W2020897165 hasPublicationYear "2010" @default.
- W2020897165 type Work @default.
- W2020897165 sameAs 2020897165 @default.
- W2020897165 citedByCount "1" @default.
- W2020897165 countsByYear W20208971652013 @default.
- W2020897165 crossrefType "proceedings-article" @default.
- W2020897165 hasAuthorship W2020897165A5014486696 @default.
- W2020897165 hasAuthorship W2020897165A5074890965 @default.
- W2020897165 hasConcept C134306372 @default.
- W2020897165 hasConcept C144024400 @default.
- W2020897165 hasConcept C153180895 @default.
- W2020897165 hasConcept C154945302 @default.
- W2020897165 hasConcept C182365436 @default.
- W2020897165 hasConcept C23224414 @default.
- W2020897165 hasConcept C2779304628 @default.
- W2020897165 hasConcept C28490314 @default.
- W2020897165 hasConcept C31510193 @default.
- W2020897165 hasConcept C31972630 @default.
- W2020897165 hasConcept C33923547 @default.
- W2020897165 hasConcept C36289849 @default.
- W2020897165 hasConcept C41008148 @default.
- W2020897165 hasConceptScore W2020897165C134306372 @default.
- W2020897165 hasConceptScore W2020897165C144024400 @default.
- W2020897165 hasConceptScore W2020897165C153180895 @default.
- W2020897165 hasConceptScore W2020897165C154945302 @default.
- W2020897165 hasConceptScore W2020897165C182365436 @default.
- W2020897165 hasConceptScore W2020897165C23224414 @default.
- W2020897165 hasConceptScore W2020897165C2779304628 @default.
- W2020897165 hasConceptScore W2020897165C28490314 @default.
- W2020897165 hasConceptScore W2020897165C31510193 @default.
- W2020897165 hasConceptScore W2020897165C31972630 @default.
- W2020897165 hasConceptScore W2020897165C33923547 @default.
- W2020897165 hasConceptScore W2020897165C36289849 @default.
- W2020897165 hasConceptScore W2020897165C41008148 @default.
- W2020897165 hasLocation W20208971651 @default.
- W2020897165 hasOpenAccess W2020897165 @default.
- W2020897165 hasPrimaryLocation W20208971651 @default.
- W2020897165 hasRelatedWork W1503813329 @default.
- W2020897165 hasRelatedWork W1509290147 @default.
- W2020897165 hasRelatedWork W1987674135 @default.
- W2020897165 hasRelatedWork W2011502238 @default.
- W2020897165 hasRelatedWork W2014141335 @default.
- W2020897165 hasRelatedWork W2044495222 @default.
- W2020897165 hasRelatedWork W2058594077 @default.
- W2020897165 hasRelatedWork W2079390261 @default.
- W2020897165 hasRelatedWork W2084428068 @default.
- W2020897165 hasRelatedWork W2109832079 @default.
- W2020897165 hasRelatedWork W2129542202 @default.
- W2020897165 hasRelatedWork W2143484718 @default.
- W2020897165 hasRelatedWork W2151837145 @default.
- W2020897165 hasRelatedWork W2162208231 @default.
- W2020897165 hasRelatedWork W2369113474 @default.
- W2020897165 hasRelatedWork W2378735518 @default.
- W2020897165 hasRelatedWork W2535966227 @default.
- W2020897165 hasRelatedWork W3144946498 @default.
- W2020897165 hasRelatedWork W2081143638 @default.
- W2020897165 hasRelatedWork W2110915074 @default.
- W2020897165 isParatext "false" @default.
- W2020897165 isRetracted "false" @default.
- W2020897165 magId "2020897165" @default.
- W2020897165 workType "article" @default.