Publication: 3d facial verification using stereo vision
| datacite.subject.fos | oecd::Engineering and technology::Electrical engineering, Electronic engineering, Information engineering | |
| dc.contributor.author | Tai, Shu Worn | |
| dc.date.accessioned | 2024-07-03T07:11:13Z | |
| dc.date.available | 2024-07-03T07:11:13Z | |
| dc.date.issued | 2010-04-01 | |
| dc.description.abstract | Face recognition has been a focus in research for the last couple of decades because of its wide potential applications and its importance to meet the security needs of today’s world. This project proposes a face recognition system that uses passive stereo vision to capture three-dimensional (3D) facial information and 3D matching using a simple Sum of Squared Difference (SSD) algorithm. So far, the reported 3D face recognition techniques assume the use of active 3D measurement for 3D facial capture. However, active methods employ structured illumination (structure projection, phase shift, gray-code demodulation, etc.) or laser scanning, which is not desirable in many human recognition applications. An advantage of passive method is that it costs lower than active method. This system uses a stereo camera to locate, track, and recognize a person’s face. This algorithm improves state-of-the-art monocular 2D object recognition techniques by additionally considering the facial 3D surface, which is relatively stable under different lighting conditions. First, faces are detected and their surfaces are reconstructed from the stereo images. Afterwards, a 3D face is composed by joining 2D image data and appropriate depth data. The 3D face is then decomposed into its principal components. The principal components are used to recognize a 3D face by comparing characteristics of the current face to those of known individuals in a database. The result is an efficient and accurate face recognition algorithm. | |
| dc.identifier.uri | https://erepo.usm.my/handle/123456789/19579 | |
| dc.language.iso | en | |
| dc.title | 3d facial verification using stereo vision | |
| dc.type | Resource Types::text::report | |
| dspace.entity.type | Publication | |
| oairecerif.author.affiliation | Universiti Sains Malaysia |