side view face recognition using di khiyal malik (5 risultati)

Paperback. Condizione: Brand New. 80 pages. 8.66x5.91x0.19 inches. In Stock.

Taschenbuch. Condizione: Neu. Neuware -The recent years have seen an increase in the growth of face recognition for computer aided identification. Majority of the processes and products developed including the traditional Viola Jones algorithm coupled with re ranking is successfully being applied on all frontal faces. Face detection remains a challenge because of variations in facade, illumination and expression. Problems arise particularly when searching for an image in the database containing side view face images. This study focuses on side-view profiles keeping in mind the current needs of forensics, census departments, police forces, and an array of government organization as well as the students studying data security. The literature survey explains various techniques currently in use to detect a front view face images. The statement of research problem identifies the challenges of detecting side view images. The proposed solution takes into consideration 15 automatically generated facial landmarks; mainly ears as an additional feature. Preprocessing is applied to the registered images to remove the background. A baseline algorithm is used and then a nearest neighbor searching scheme is applied.Books on Demand GmbH, Überseering 33, 22297 Hamburg 80 pp. Englisch.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The recent years have seen an increase in the growth of face recognition for computer aided identification. Majority of the processes and products developed including the traditional Viola Jones algorithm coupled with re ranking is successfully being applied on all frontal faces. Face detection remains a challenge because of variations in facade, illumination and expression. Problems arise particularly when searching for an image in the database containing side view face images. This study focuses on side-view profiles keeping in mind the current needs of forensics, census departments, police forces, and an array of government organization as well as the students studying data security. The literature survey explains various techniques currently in use to detect a front view face images. The statement of research problem identifies the challenges of detecting side view images. The proposed solution takes into consideration 15 automatically generated facial landmarks; mainly ears as an additional feature. Preprocessing is applied to the registered images to remove the background. A baseline algorithm is used and then a nearest neighbor searching scheme is applied. 80 pp. Englisch.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Khiyal Malik Sikander HayatProf. Dr. Malik Sikandar Hayat Khiyal is currently a Professor at Faculty of Computer Science, Preston University, Islamabad. He remained Chairman Department of Computer Sciences and Software Engineering in.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The recent years have seen an increase in the growth of face recognition for computer aided identification. Majority of the processes and products developed including the traditional Viola Jones algorithm coupled with re ranking is successfully being applied on all frontal faces. Face detection remains a challenge because of variations in facade, illumination and expression. Problems arise particularly when searching for an image in the database containing side view face images. This study focuses on side-view profiles keeping in mind the current needs of forensics, census departments, police forces, and an array of government organization as well as the students studying data security. The literature survey explains various techniques currently in use to detect a front view face images. The statement of research problem identifies the challenges of detecting side view images. The proposed solution takes into consideration 15 automatically generated facial landmarks; mainly ears as an additional feature. Preprocessing is applied to the registered images to remove the background. A baseline algorithm is used and then a nearest neighbor searching scheme is applied.