A Neuro-fuzzy Approach to User Attention Recognition (original) (raw)

References

  1. Voit, M., Nickel, K., Stiefelhagen, R.: Multi-view head pose estimation using neural networks. In: Second Canadian Conference on Computer and Robot Vision (CRV), Victoria, BC, Canada, pp. 347–352. IEEE Computer Society, Los Alamitos (2005)
    Chapter Google Scholar
  2. Mao, Y., Suen, C.Y., Sun, C., Feng, C.: Pose estimation based on two images from different views. In: Eighth IEEE Workshop on Applications of Computer Vision (WACV), Washington, DC, USA, p. 9. IEEE Computer Society, Los Alamitos (2007)
    Chapter Google Scholar
  3. Beymer, D., Flickner, M.: Eye gaze tracking using an active stereo head. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), Madison, WI, USA, vol. 2, pp. 451–458. IEEE Computer Society, Los Alamitos (2003)
    Google Scholar
  4. Meyer, A., Böhme, M., Martinetz, T., Barth, E.: A single-camera remote eye tracker. LNCS (LNAI), pp. 208–211. Springer, Heidelberg (2006)
    Google Scholar
  5. Hennessey, C., Noureddin, B., Lawrence, P.D.: A single camera eye-gaze tracking system with free head motion. In: Proceedings of the Eye Tracking Research & Application Symposium (ETRA), San Diego, California, USA, pp. 87–94. ACM, New York (2006)
    Chapter Google Scholar
  6. Gee, A., Cipolla, R.: Non-intrusive gaze tracking for human-computer interaction. In: Int. Conference on Mechatronics and Machine Vision in Pract., Toowoomba, Australia, pp. 112–117 (1994)
    Google Scholar
  7. Gourier, N., Hall, D., Crowley, J.: Estimating face orientation from robust detection of salient facial features. In: International Workshop on Visual Observation of Deictic Gestures (ICPR), Cambridge, UK (2004)
    Google Scholar
  8. Seo, K., Cohen, I., You, S., Neumann, U.: Face pose estimation system by combining hybrid ica-svm learning and re-registration. In: 5th Asian Conference on Computer Vision, Jeju, Korea (2004)
    Google Scholar
  9. Stiefelhagen, R.: Estimating Head Pose with Neural Networks - Results on the Pointing 2004 ICPR Workshop Evaluation Data. In: Pointing 2004 Workshop (ICPR), Cambridge, UK (August 2004)
    Google Scholar
  10. Daugman, J.: High confidence visual recognition of persons by a test of statistical independence. IEEE Trans. Pattern Anal. Mach. Intell. 15(11), 1148–1161 (1993)
    Article Google Scholar
  11. Deng, J.Y., Lai, F.: Region-based template deformation and masking for eye-feature extraction and description. Pattern Recognition 30(3), 403–419 (1997)
    Article Google Scholar
  12. Viola, P.A., Jones, M.J.: Rapid object detection using a boosted cascade of simple features. In: Conference on Computer Vision and Pattern Recognition (CVPR), Kauai, HI, vol. 1, pp. 511–518 (December 2001)
    Google Scholar
  13. Asteriadis, S., Nikolaidis, N., Pitas, I., Pardàs, M.: Detection of facial characteristics based on edge information. In: Second International Conference on Computer Vision Theory and Applications(VISAPP), Barcelona, Spain
    Google Scholar
  14. Zhou, Z.H., Geng, X.: Projection functions for eye detection. Pattern Recognition 37(5), 1049–1056 (2004)
    Article MATH Google Scholar
  15. Chiu, S.L.: Fuzzy Model Identification Based on Cluster Estimation. Journal of Intelligent and Fuzzy Systems 2(3) (1994)
    Google Scholar
  16. Jang, J.S.R.: ANFIS: Adaptive-Network-Based Fuzzy Inference System. IEEE Transactions on Systems, Man, and Cybernetics 23, 665–684 (1993)
    Article Google Scholar

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