Face recognition has been an active research area over the last 30 years. The face is our primary focus of attention in social intercourse, playing a major role in conveying identity and emotion. Although the ability to infer intelligence or character from facial appearance is suspect, the human ability to recognize faces is remarkable. We can recognize thousands of faces learned throughout our lifetime and identify familiar faces at a glance even after years of separation. This skill is quite robust, despite large changes in the visual stimulus due to viewing conditions, expression, aging, and distractions such as glasses or changes in hair style. In this book, Laplacian faces which uses linear projective projection is studied and finally enhanced before accuracy. LPP is designed for preserving local structure; it is likely that a nearest neighbour search in the low dimensional space will yield similar results to that in the high dimensional space. LPP’s are linear projective maps that arise by solving a variational problem that optimally preserves the neighborhood structure of the data set. Finally the algorithm is modified to yield better results in terms of time and accuracy.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Face recognition has been an active research area over the last 30 years. The face is our primary focus of attention in social intercourse, playing a major role in conveying identity and emotion. Although the ability to infer intelligence or character from facial appearance is suspect, the human ability to recognize faces is remarkable. We can recognize thousands of faces learned throughout our lifetime and identify familiar faces at a glance even after years of separation. This skill is quite robust, despite large changes in the visual stimulus due to viewing conditions, expression, aging, and distractions such as glasses or changes in hair style. In this book, Laplacian faces which uses linear projective projection is studied and finally enhanced before accuracy. LPP is designed for preserving local structure; it is likely that a nearest neighbour search in the low dimensional space will yield similar results to that in the high dimensional space. LPP’s are linear projective maps that arise by solving a variational problem that optimally preserves the neighborhood structure of the data set. Finally the algorithm is modified to yield better results in terms of time and accuracy.
A Post Graduate(M.Tech) from the M.M.University, Mullana with specialization in Image Processing having a 07 years of experience in teaching. My interests include Pattern Finding and Computer Communication Networks. I am also CCNA certified.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Face recognition has been an active research area over the last 30 years. The face is our primary focus of attention in social intercourse, playing a major role in conveying identity and emotion. Although the ability to infer intelligence or character from facial appearance is suspect, the human ability to recognize faces is remarkable. We can recognize thousands of faces learned throughout our lifetime and identify familiar faces at a glance even after years of separation. This skill is quite robust, despite large changes in the visual stimulus due to viewing conditions, expression, aging, and distractions such as glasses or changes in hair style. In this book, Laplacian faces which uses linear projective projection is studied and finally enhanced before accuracy. LPP is designed for preserving local structure; it is likely that a nearest neighbour search in the low dimensional space will yield similar results to that in the high dimensional space. LPP s are linear projective maps that arise by solving a variational problem that optimally preserves the neighborhood structure of the data set. Finally the algorithm is modified to yield better results in terms of time and accuracy. N° de réf. du vendeur 9783659234316
Quantité disponible : 2 disponible(s)
Vendeur : moluna, Greven, Allemagne
Kartoniert / Broschiert. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Gupta GauravA Post Graduate(M.Tech) from the M.M.University, Mullana with specialization in Image Processing having a 07 years of experience in teaching. My interests include Pattern Finding and Computer Communication Networks. I am . N° de réf. du vendeur 5141821
Quantité disponible : Plus de 20 disponibles
Vendeur : preigu, Osnabrück, Allemagne
Taschenbuch. Etat : Neu. Registration And Classification Of Face Images | Face Recognition | Gaurav Gupta (u. a.) | Taschenbuch | Englisch | LAP Lambert Academic Publishing | EAN 9783659234316 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de réf. du vendeur 106262480
Quantité disponible : 5 disponible(s)
Vendeur : Mispah books, Redhill, SURRE, Royaume-Uni
Paperback. Etat : Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book. N° de réf. du vendeur ERICA79636592343116
Quantité disponible : 1 disponible(s)