3D face reconstruction techniques: Passive methods

Title

3D face reconstruction techniques: Passive methods

Creator

John S.; Danti A.

Description

In the recent literature, 3D face reconstruction received wide interest and has become one of the significant areas of research. 3D face reconstruction provides in depth details on geometrics, texture and color of the face, which are utilized in different applications. It supports a multitude of applications, ranging from face recognition and surveillance to medical imaging, gaming, animation, and virtual reality. This paper attempts to consolidate the research works that have happened in the history of 3D face reconstruction. Also, we try to classify the existing methods based on the input for the process. The databases used in the recent works are discussed and the performance evaluation of methods on different databases is analyzed. The challenges addressed in recent studies are mainly focused on the faster reconstruction of 3D Images, improved accuracy of reconstructed images, human pose identification, image reproduction with higher resolution. Researchers have also tried to address occlusion related problems. Passive methods, used by different researchers are analyzed and their effects on different parameters are discussed in this work. Finally, possible future areas for improvement in terms of reconstructions are presented for the benefit of researchers. BEIESP.

Source

International Journal of Recent Technology and Engineering, Vol-8, No. 2, pp. 4354-4364.

Date

2019-01-01

Publisher

Blue Eyes Intelligence Engineering and Sciences Publication

Subject

3D face modeling; 3D face reconstruction; Computer vision; Image processing; Machine learning

Coverage

John S., Department of Computer Science & Engineering, Faculty of Engineering, Christ (Deemed to be University), Bangalore, India; Danti A., Department of Computer Science & Engineering, Faculty of Engineering, Christ (Deemed to be University), Bangalore, India

Rights

All Open Access; Gold Open Access

Relation

ISSN: 22773878

Format

Online

Language

English

Type

Article

Identifier

https://doi.org/10.35940/ijrte.B3152.078219

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85071870147&doi=10.35940%2fijrte.B3152.078219&partnerID=40&md5=3d70f05bcca1d3c38767f99eb4cf2fe3