Tools
Tools
Porto, LF, Lima, LNC, Pinheiro Flores, M, Valsecchi, A, Ibanez, O, Machado, CEP and Vidal, FDB (2019) Automatic cephalometric landmarks detection on frontal faces: An approach based on supervised learning techniques. Digital Investigation, 30. pp. 108-116. ISSN 1742-2876
|
Text
Porto_2019_Automatic cephalometric landmarks detection on frontal faces.pdf - Accepted Version Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (1MB) | Preview |
Abstract
Facial landmarks are employed in many research areas such as facial recognition, craniofacial identification, age and sex estimation among the most important. In the forensic field, the focus is on the analysis of a particular set of facial landmarks, defined as cephalometric landmarks. Previous works demonstrated that the descriptive adequacy of these anatomical references for an indirect application (photo-anthropometric description) increased the marking precision of these points, contributing to a greater reliability of these analyzes. However, most of them are performed manually and all of them are subjectivity inherent to the expert examiners. In this sense, the purpose of this work is the development and validation of automatic techniques to detect cephalometric landmarks from digital images of frontal faces in forensic field. The presented approach uses a combination of computer vision and image processing techniques within a supervised learning procedures. The proposed methodology obtains similar precision to a group of human manual cephalometric reference markers and result to be more accurate against others state-of-the-art facial landmark detection frameworks. It achieves a normalized mean distance (in pixel) error of 0.014, similar to the mean inter-expert dispersion (0.009) and clearly better than other automatic approaches also analyzed along of this work (0.026 and 0.101).
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | 0899 Other Information and Computing Sciences |
| Subjects: | N Fine Arts > N Visual arts (General) For photography, see TR Q Science > QA Mathematics > QA75 Electronic computers. Computer science R Medicine > RA Public aspects of medicine > RA1001 Forensic Medicine. Medical jurisprudence. Legal medicine |
| Divisions: | Art & Design |
| Publisher: | Elsevier |
| Date Deposited: | 11 Dec 2019 11:17 |
| Last Modified: | 04 Sep 2021 08:17 |
| DOI or ID number: | 10.1016/j.diin.2019.07.008 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/11882 |
 |
View Item |