Automatic landmarking on 2.5D face range images
This project presents a novel approach for automatic landmarking process on face range images. The approach consists of feature extraction and feature localisation methods. In recent years, methods to improve existing face processing applications have increased rapidly. This includes automatic la...
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis |
| Language: | English |
| Published: |
2014
|
| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/9115/1/Pui%20Suk%20Ting%20ft.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | This project presents a novel approach for automatic landmarking process on face
range images. The approach consists of feature extraction and feature localisation methods.
In recent years, methods to improve existing face processing applications have increased
rapidly. This includes automatic landmarking method which could be an important
intermediary step for many face processing applications, such as for face recognition, face
analysis and etc. The approach aims to locate facial feature points automatically, such as the
nose tip, the mouth corners, chin, etc., without the intervention of human. Automatic
landmarking holds a number of added advantages over manual landmarking especially if
dataset is large, the landmark selection would be less time consuming. Identifying features on
a face automatically may be a challenging process for computing. Our human vision system
can perceive salient feature easily without any difficulties. For instance, a human is able to
detect the eyes, the nose tip and/or the mouth of a person at a first glance. However, a
computer system is unable to do such task easily and effortlessly. Therefore, a method to
automatically detect and label landmarks on the features of the face is developed. Firstly,
features or primitive surface types are extracted from range images. The primitive surfaces
are derived using Mean (H) and Gaussian (K) curvatures from a down-sampled by Gaussian
Pyramid approach. Otsu’s algorithm is used to place landmark on the extracted facial
features and/or regions. In summary, we have successfully implemented an automatic
landmarking method and an interactive tool has been developed to ease the visualisation of
the overall processes. |
|---|