Skip to main content
Log in

Gaze correction using feature-based view morphing and performance evaluation

  • Original Paper
  • Published:
Signal, Image and Video Processing Aims and scope Submit manuscript

Abstract

Lack of eye gaze in the video conferencing system severely hinders immersive and comfortable communication. In this paper, we propose an eye gaze correction system for immersive video conferencing. Our system consists of a full HD display and two cameras mounted on the top and bottom of the display. In order to correct the eye gaze, we warp two captured images from their original positions to a virtual position, respectively. After we implement view morphing between corresponding triangles, we obtain a gaze-corrected image by interpolating the two morphed images. We also present a subjective evaluation method to measure the performance of our approach. Experimental results show that our system is effective in generating natural gaze-corrected images.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

References

  1. Gemmell, J., Toyama, K., Zitnick, C.L., Kang, T., Seitz, S.: Gaze awareness for video-conferencing: a software approach. IEEE MultiMed. 4, 26–35 (2000)

    Google Scholar 

  2. Ott, M., Lewis, J.P., Cox, I.: Teleconferencing eye contract using a virtual camera. In: Proceeding CHI ‘93 INTERACT ‘93 and CHI ‘93 Conference Companion on Human Factors in Computing Systems, pp. 109–110. ACM, NY (1993)

  3. Yang, R., Zhang, Z.: Eye gaze correction with stereovision for video-teleconferencing. In: Computer Vision—ECCV, pp. 479–494 (2002)

  4. Ma, X., Deng, Z.: Natural eye motion synthesis by modeling gaze-head coupling. In: 2009 IEEE Virtual Reality Conference, Lafayette, LA, pp. 143–150

  5. Kuster, C., Popa, T., Bazin, J.C., Gotsman, C., Gross, M.: Gaze correction for home video conferencing. ACM Trans. Gr. 31(6), 174 (2012)

    Article  Google Scholar 

  6. Kjeldskov, J., Smedegård, J.H., Nielsen, T.S., Skov, M.B., Paay, J.: EyeGaze: enabling eye contact over video. In: Proceedings on Advanced Visual Interfaces, pp. 105–112 (2014)

  7. Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision. Cambridge university press (2003)

  8. Zhang, Z.: A flexible new technique for camera calibration. Pattern Anal. Mach. Intell. 22(11), 1330–1334 (2000)

    Article  Google Scholar 

  9. Jung, J.I., Ho, Y.S.: Improved polynomial model for multi-view image color correction. J. Korean Inst. Commun. Inf. Sci. 38(10), 881–886 (2013)

    Google Scholar 

  10. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60(2), 91–110 (2004)

    Article  Google Scholar 

  11. Wilson, P.I., Fernandez, J.: Facial feature detection using Haar classifiers. J. Comput. Sci. Coll. 21(4), 127–133 (2006)

    Google Scholar 

  12. Seitz, S.M., Dyer, C.R.: Viewing morphing: uniquely predicting scene appearance from basisimages. In: Prof. DARPA Image Understanding Workshop, pp 881–887 (1997)

  13. Canny, J.: A computational approach to edge detection. Pattern Anal. Mach. Intell. 6, 679–698 (1986)

    Article  Google Scholar 

  14. Shin, D.W., Ho, Y.S. Implementation of 3D object reconstruction using a pair of kinect cameras. In: Proceedings on Asia-Pacific Signal and Information Processing Association, pp. 1–4 (2014)

  15. Ho, Y.S., Jang, W.S.: Gaze correction using 3D video processing for videoconferencing. In: Signal and Information Processing (ChinaSIP), pp. 496–499 (2015)

  16. Ko, E., Jang, W.S., Ho, Y.S.: Eye gaze correction for video conferencing using Kinect v2. In: Advances in Multimedia Information Processing, pp. 571–578 (2015)

Download references

Acknowledgments

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (No. 2011-0030079)

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Eu-Tteum Baek.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Baek, ET., Ho, YS. Gaze correction using feature-based view morphing and performance evaluation. SIViP 11, 187–194 (2017). https://doi.org/10.1007/s11760-016-0918-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11760-016-0918-1

Keywords

Navigation