Journal of information and communication convergence engineering

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
권호 표지

Visual Modeling and Content-based Processing for Video Data Storage and Delivery

  • Hwang Jae-Jeong (School of Electronic and Information Engineering, Kunsan National University) ;
  • Cho Sang-Gyu (School of Electronic and Information Engineering, Kunsan National University)
  • Published : 2005.03.01
Download PDF
⟨ Previous Next ⟩

Abstract

In this paper, we present a video rate control scheme for storage and delivery in which the time-varying viewing interests are controlled by human gaze. To track the gaze, the pupil's movement is detected using the three-step process : detecting face region, eye region, and pupil point. To control bit rates, the quantization parameter (QP) is changed by considering the static parameters, the video object priority derived from the pupil tracking, the target PSNR, and the weighted distortion value of the coder. As results, we achieved human interfaced visual model and corresponding region-of-interest rate control system.

Keywords

References

  1. S. Chien and I. Choi, 'Face and Facial Landmarks Location Based on Log-Polar Mapping', First IEEE International Workshop, BMCV 2000, 2000
  2. R. Chellappa, Wilson, C. L. Sirohey, S. Sirohey, 'Human and machine recognition of faces: A Survey', Proc. of IEEE, vol. 83,1995, pp. 705-740 https://doi.org/10.1109/5.381842
  3. K. Sung and T. Pcggio, 'Example-based learning for view-based human face detection', IEEE Trans. Pattern Anal. Mach. Intelligence, vol. 20, 1998, pp. 39-51 https://doi.org/10.1109/34.655648
  4. P. Viola and M. Jones, 'Rapid object detection using a boosted cascade of simple features', IEEE CVPR, 2001 https://doi.org/10.1109/CVPR.2001.990517
  5. R. Lienhart and J. Maydt, 'An extended set of Haarlike features for rapid object detection', IEEE ICIP 2002, vol. 1,2002, pp. 900-903 https://doi.org/10.1109/ICIP.2002.1038171
  6. E. Hjelmas and B. K. Low, 'Face detection: A survey', Computer Vision and Image Understanding, vol. 83, 2001, pp. 236-274 https://doi.org/10.1006/cviu.2001.0921
  7. H. A. Rowley, S. Baluja, and T. Kanade, 'Neural network-based face detection', IEEE Trans PAMI, vol. 20, 1998, pp. 23-38 https://doi.org/10.1109/34.655647
  8. R. Rrunelli and T. Poggio, 'Face recognition: features versus templates', IEEE Trans. PAMI, vol. 20, 1993,pp. 1042-1052
  9. S. Z. Li and J. Lu, 'Face recognition using the nearest feature line method', IEEE. Trans. on Neural Network, vol. 10, 1999, pp. 439-443 https://doi.org/10.1109/72.750575
  10. P. Sinha, 'Object recognition via image invariant: A case study', Investigative Oph-thalmology and Visual Science, vol. 35, 1994, pp. 1735-1740
  11. M. H. Yang, D. Kriegman and N. Ahuja, 'Detecting faces in images: A survey', IEEE Trans. PAMI, vol. 24, 2002, pp. 34-58 https://doi.org/10.1109/34.982883
  12. Y. Freund and R. E. Schapire, 'A decision-theoretic generalization of on-line learning and an application to boosting', Computational Learning Theory: Eurocolt'95, 1995, pp. 23-37
  13. R. Lienhart, A. Kuranov and V. Ppsarevsky, 'Empirical analysis of detection cascades of boosted classifiers for rapid object detection', DAGM'03, 25th Pattern Recognition Symposium, 2003
  14. T. Weigand, et al., 'Rate-distortion optimized mode selection for very low bit-rate video coding and emerging H.263 standard,' IEEE Trans. on CSVT, vol. 6, Apr. 1996, pp. 182-190
  15. J. Lee and B. W. Dickenson, 'Rate-distortion optimized frame type selection for MPEG encoding,' IEEE Trans. on CSVT, vol. 7, June 1997, pp. 501-510
  16. T. Chiang and Y. Q. Zhang, 'A new rate control scheme using quadratic rate-distortion modeling,' IEEE Trans. on CSVT, vol. 7, Feb. 1997, pp. 246-250
  17. A. Vetro, H. Sun, and Y. Wang, 'MPEG-4 rate control for multiple video objects,' IEEE Trans. on CSVT, vol. 9, Feb. 1999, pp. 186-199
  18. J. I. Ronda, M. Eckert, F. Jaureguizar, and N. Garcia, 'Rate Control and Bit Allocation for MPEG-4', IEEE Trans. Circuits Syst. Video Technol., vol. 9, Dec. 1999, pp. 1243-1258 https://doi.org/10.1109/76.809159