Please use this identifier to cite or link to this item:
http://hdl.handle.net/123456789/235
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Savakar, Dayanand G. | - |
dc.contributor.author | Hosur, Ravi Hosur | - |
dc.date.accessioned | 2023-11-24T09:32:01Z | - |
dc.date.available | 2023-11-24T09:32:01Z | - |
dc.date.issued | 2018-03 | - |
dc.identifier.issn | 25253–25273 | - |
dc.identifier.uri | http://hdl.handle.net/123456789/235 | - |
dc.description.abstract | Three-dimensional object construction has seen a great deal of activity in the past decade, as has been pointed out in recent surveys, with the advancement of technology and easy availability of the depth sensors the 3D scanning technology has taken off. A wide range of commercial sensors such as Intel RealSense, Microsoft Kinect are being widely used for real time 3D capturing. Efficient 3D face scanning is one of the important areas of 3D scanning. 3D printer compatible texture supported scanning has a wide range of commercial applications. Such methods are also being used for 3D avatars and character izations for games. Even though several commercial grade applications are available, most of the techniques suffer from background and light variations. Therefore an efficient face scanning technique is of extreme importance. In this paper we propose a 3D face scanning method based on Intel RealSense technology that combines 3D face detection, background segmentation and 3D mesh mapping to produce realistic 3D face model along with texture export. Further the models then can be manipulated using any 3D editing software along with texture and wireframe manipulation. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | Springer Nature | en_US |
dc.subject | 3D image .RealSense . Depth . Segmentation .Texture . Projection . Meshing . Point cloud | en_US |
dc.title | A relative 3D scan and construction for face using meshing algorithm | en_US |
dc.type | Article | en_US |
Appears in Collections: | F P |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Paper2.pdf | 6.95 MB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.