Lingua: Inglese
Editore: LAP Lambert Academic Publishing, 2011
ISBN 10: 3845428899 ISBN 13: 9783845428895
Da: preigu, Osnabrück, Germania
EUR 43,30
Quantità: 5 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. Face Localization, Color Images and Postural Degradation | Face Recognition, Postural Equilibrium, Detection and Statistical Analysis | Chandan Srivastava | Taschenbuch | Englisch | LAP Lambert Academic Publishing | EAN 9783845428895 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3845428899 ISBN 13: 9783845428895
Da: moluna, Greven, Germania
EUR 41,67
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Srivastava ChandanChandan Srivastava is doctoral research fellow at Universitat Rovira i Virgili, Tarragona, Spain. He did his master research at the Department of Electrical Engineering, IIT Kanpur, India and UTT Troyes, France. His.
Lingua: Inglese
Editore: LAP Lambert Academic Publishing, 2011
ISBN 10: 3845428899 ISBN 13: 9783845428895
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 49,59
Quantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The present research explores experimental evaluation of the face localization method using skin color based approach and works on the color images. This method first corrects the used bias by lighting compensation techniques which automatically estimate the references white pixels. The outcome difficulty of localizing the low and high luma skin tones is performed by applying a nonlinear transformation to the YCbCr color space. Proposed method is able to localize skin regions over the face images and thereby identifies the candidate based on the skin patches. The present study continues towards the identification of the most suitable unique class of model and the parameter reductions for elderly fall prevention.