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Development of new databases contributing much among researchers for solving many challenging tasks that might have an important role during the implementation of efficient algorithms to handle all difficulties for an automatic system. In this paper, authors have introduced the issues and approaches that have been considered during image acquisition procedure during designing of own face database. This database consists of almost all the challenges in the domain of computer vision especially face recognition. Acquisition of database’s images are done in our own institute’s laboratory with variations of facial actions (i.e. movement of facial units, expression), illumination, occlusion, as well as a pose. Along with the 3D face images, corresponding 2D face images have also been captured using Structured Light Scanner (SLS). Particularly, this image acquisition technique is not harmful as laser scanner does. Moreover, authors have made the visualization of practical representation of laboratory setup within this article that would again be helpful to the researchers for better understanding the image acquisition procedure in detail. In this databases, authors have accomplished the X, Y planes along with range face image and corresponding 2D image of human face.
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Ganguly, S., Bhattacharjee, D., and Nasipuri, M.: 3D Face Recognition from Range Images Based on Curvature Analysis. In: ICTACT Journal on Image and Video Processing, Vol. 04, Issue. 03, pp. 748–753 (2014).
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3D RMA face database, http://www.sic.rma.ac.be/~beumier/DB/3d_rma.html. Retrieved 26th July, 2014.
Univ. of York 1 database, http://www-users.cs.york.ac.uk/~tomh/3DfaceDatabase.html. Retrieved 22nd July, 2014.
Univ. of York 2 database, http://www-users.cs.york.ac.uk/~tomh/3DfaceDatabase.html. Retrieved 22nd July, 2014.
GavabDB database, http://www.gavab.etsii.urjc.es/recursos_en.html. Retrieved 16th August, 2014.
Frav3D database, http://archive.today/B1WeX. Retrieved 16th August, 2014.
Bosphorus database, http://bosphorus.ee.boun.edu.tr/Home.aspx. Retrieved 16th August, 2014.
BJUT-3D Chinese face database, http://www.bjut.edu.cn/sci/multimedia/mul-lab/3dface/facedatabase.htm. Retrieved 24th July, 2014.
CASIA-3D FaceV1, http://www.idealtest.org/dbDetailForUser.do?id=8. Retrieved 24th July, 2014.
Texas 3D face database, http://live.ece.utexas.edu/research/texas3dfr/. Retrieved 23rd July, 2014.
UMB-DB face database, http://www.ivl.disco.unimib.it/umbdb/. Retrieved 22nd July, 2014.
ND2006 3D face database, http://www3.nd.edu/~cvrl/CVRL/Data_Sets.html. Retrieved 22nd July, 2014.
FRGC v.2 face database, http://www3.nd.edu/~cvrl/CVRL/Data_Sets.html. Retrieved 22nd July, 2014.
3D Facial Expression Database, http://pdf.aminer.org/000/262/410/d_geometric_databases_for_mechanical_engineering.pdf. Retrieved 16th July, 2014.
3D Tec database of 3D Twins Expression, http://www3.nd.edu/~cvrl/CVRL/Data_Sets.html. Retrieved 22nd July, 2014.
BFM database, http://faces.cs.unibas.ch/bfm/main.php?nav=1-0&id=basel_face_model. Retrieved 1st August, 2014.
- Issues and Approaches to Design of a Range Image Face Database
- Springer India
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