الفهرس 
Human Age EstimationOnly 14 pages are availabe for public view
 |  | from | 94 |  |  |
| | | from | 94 | | |
Abstract
Estimating human age from his images is a problem that has recently gained attention from the computer vision community due to its numerous applications as well as the challenges that face a satisfactory solution. Beside traditional challenges in captured facial images under uncontrolled settings such as different lighting, varying poses and expressions, aging effects on appearance depends on many other factors such as life style. The main goal of this thesis is to estimate the human age for the people that are exposed to Botox injections through building an age estimation model called Human Injected by Botox Age Estimation (HIBAE) based on the characteristic and information that can be extracted from the human face images using ASM, SURF and SVM. HIBAE proposed model was trained by a crossover of PAL database and 60 images collected from the internet of people that were exposed to Botox, and tested using a crossover of FACES94 database and 20 images of people that were exposed to Botox. HIBAE had showed superiority through performance testing over the state-of-the-art.