Open source library-based 3D face point cloud generation

Bulent Bayram, Taskin Ozkan, Hatice Catal Reis*, Tolga Bakirman, Ibrahim Cetin, Dursun Zafer Seker

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Three dimensional (3D) face and body modeling is widely used in various fields such as plastic surgery, diagnosis of facial or body anomalies, 3D computer games and 3D simulation software. Since, commercial 3D face and body scanners are usually expensive, an alternative solution with lower cost is highly desirable. The objective of this study is to create 3D facial point cloud using Semi Global Image Matching method with minimum number of images utilizing a cost effective method. A non-metric Canon 600D camera with 18 megapixels resolution (3456 × 5184) and 60 mm macro lens have been used for face imaging that have been taken from a distance of 120 cm. Five faces have been modeled by the developed algorithm and scanned by David SLS-2 structured light system for accuracy assessment. Open source Cloud Compare software has been used for comparing the results of proposed method with the structured light system. The mean accuracy of five faces obtained as 90.5%. It has been observed that illumination conditions, uncontrolled movements of face or body, hair and eyebrow have negative impacts on the obtained results. The sufficiency of Semi global image matching method has been tested to create dense point cloud data from three stereo pairs for 3D facial modelling.

Original languageEnglish
Pages (from-to)1875-1887
Number of pages13
JournalChiang Mai Journal of Science
Volume45
Issue number4
Publication statusPublished - Jul 2018

Bibliographical note

Publisher Copyright:
© 2018, Chiang Mai University. All rights reserved.

Keywords

  • 3D face modeling
  • Open source image processing library
  • Optic laser scanning
  • Photogrammetry
  • Point cloud

Fingerprint

Dive into the research topics of 'Open source library-based 3D face point cloud generation'. Together they form a unique fingerprint.

Cite this