Compact and accurate 3-D face modeling using an RGB-D camera: Let's open the door to 3-D video conference

Pavan Kumar Anasosalu, Diego Thomas, Akihiro Sugimoto

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Citations (Scopus)

Abstract

We present a method for producing an accurate and compact 3-D face model in real time using a low cost RGB-D sensor like the Kinect camera. We extend and use Bump Images for highly accurate and low memory consumption 3-D reconstruction of the human face. Bump Images are generated by representing the Cartesian coordinates of points on the face in the spherical coordinate system whose origin is the center of the head. After initialization, the Bump Images are updated in real time with every RGB-D frame with respect to the current viewing direction and head pose that are estimated using the frame-to-global-model registration strategy. While high accuracy of the representation allows to recover fine details, low memory use opens new possible applications of consumer depth cameras such as 3-D video conferencing. We validate our approach by quantitatively comparing our result with the result obtained by a commercial high resolution laser scanner. We also discuss the potential of our proposed method for a 3-D video conferencing application with existing internet speeds.

Original languageEnglish
Title of host publicationProceedings - 2013 IEEE International Conference on Computer Vision Workshops, ICCVW 2013
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages67-74
Number of pages8
ISBN (Print)9781479930227
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event2013 14th IEEE International Conference on Computer Vision Workshops, ICCVW 2013 - Sydney, NSW, Australia
Duration: Dec 1 2013Dec 8 2013

Publication series

NameProceedings of the IEEE International Conference on Computer Vision

Other

Other2013 14th IEEE International Conference on Computer Vision Workshops, ICCVW 2013
Country/TerritoryAustralia
CitySydney, NSW
Period12/1/1312/8/13

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition

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