header
Local cover image
Local cover image
Image from OpenLibrary

Exemplars combination using genetic algorithm for accurate face landmark localization / Mostafa Mohamed Izz Eldin Shehata ; Supervised Elsayed E. Hemayed ,

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Mostafa Mohamed Izz Eldin Shehata , 2014Description: 57 P. : charts , facsimiles ; 30cmOther title:
  • دمج النماذج باستخدام الخوارزميات الجينية لتحديد علامات الوجه المميزة بدقة [Added title page title]
Subject(s): Online resources: Available additional physical forms:
  • Issued also as CD
Dissertation note: Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Computer Engineering Summary: Accurate face landmarks localization is one of the fundamental steps in many computer vision problems. In this thesis we propose a method for accurately localizing these landmarks based on: (1) modeling faces as non- linear combination of exemplars; (2) the model and optimization is done using genetic algorithm to best model this problem. Performance evaluation of our EC-GA algorithm showed that our algorithm outperformed many sate-of-art methods on di{uFB00}erent public datasets
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
Holdings
Item type Current library Home library Call number Copy number Status Barcode
Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.06.M.Sc.2014.Mo.E (Browse shelf(Opens below)) Not for loan 01010110064833000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.06.M.Sc.2014.Mo.E (Browse shelf(Opens below)) 64833.CD Not for loan 01020110064833000

Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Computer Engineering

Accurate face landmarks localization is one of the fundamental steps in many computer vision problems. In this thesis we propose a method for accurately localizing these landmarks based on: (1) modeling faces as non- linear combination of exemplars; (2) the model and optimization is done using genetic algorithm to best model this problem. Performance evaluation of our EC-GA algorithm showed that our algorithm outperformed many sate-of-art methods on di{uFB00}erent public datasets

Issued also as CD

There are no comments on this title.

to post a comment.

Click on an image to view it in the image viewer

Local cover image