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Toward robust face analysis method of non-cooperative persons in stereo color image sequences

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Konferencja
International Conference on Computer Vision and Graphics ICCVG 2006 (25-27.09.2006 ; Warsaw, Poland)
Języki publikacji
EN
Abstrakty
EN
This paper describes a novel method for analyzing single faces of non-cooperative persons on the basis of stereoscopic color images. The challenges arise from the fact that the persons observed are non-cooperative, which in turn complicates further processing as facial feature extraction and tracking in image sequence. In our method, face detection is based on color-driven clustering of 3D points derived from stereo. A mesh model is registered with a post-processed face cluster, using a variant of the Iterative Closest Point algorithm [ICP]. The pose is derived from correspondence. Then, the pose and model information are used for face normalization and facial feature localization. Automatic extraction of facial features is carried out using modified Active Shape Models [ASM]. In contrast to the simple ASM, another approach is pursued in this work. It involves two modifications to the ASM, which lead to greater stability and robustness. The results show that stereo and color are powerful cues for finding the face and its pose, and for facial feature extraction under a wide range of poses, illumination types and expressions [PIE].
Rocznik
Strony
245--254
Opis fizyczny
Bibliogr. 13 poz., il.
Twórcy
autor
autor
autor
Bibliografia
  • [1] Bentley J. L.: Multidimensional binary search trees used for associative searching, ACM, 18, pp. 509-517, 1975.
  • [2] Adini Y., Moses Y., Ullman S.: Face recognition: The problem of compensating for changes in illumination direction. IEEE Transactions on Pattern Analysis and MI, 19(7):721-732, 1997.
  • [3] Jacobs D., Belhumeur P., Basri R.: Comparing images under variable illumination. IEEE Conf. on CV and Pattern Recognition, pp. 610-617, 1998.
  • [4] Blackburn D., Bone M., Phillips P.: Facial recognition vendor test 2000: Evaluation report, 2000.
  • [5] Phillips P. J., Moon H., Rizvi S., Rauss P.: The FERET evaluation methodology for face recognition algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(10):1090-1104, 2000.
  • [6] Zitnick C., Kanade T.: A cooperative algorithm for stereo matching and occlusion detection, IEEE Transactions on Pattern Analysis and Machine Intelligence (MI), Vol. 22, No. 7, pp. 675-684, 2000.
  • [7] Gross R., Shi J., Chon J.: Quo vadis face recognition? 3th Workshop on empirical evaluation methods in Computer Vision, 2001.
  • [8] Rusinkiewicz S., Levoy M.: Efficient variants of the ICP algorithm, Proc. of the 3rd Int. Conf. on 3D Digital Imaging & Modeling, pp. 145-152, 2001.
  • [9] Brown L., Tian Y.: Comparative study of coarse head pose estimation, IEEE Workshop on Motion and Video Computing, Orlando, pp. 125-130, 2002.
  • [10] Li S. Z., Jain A. K.: Handbook of Face Recognition, ISBN: 0-387-40595-X, 2005.
  • [11] Malassiotis S., Strintzis M. G.: Robust Real-time 3D Head Pose Estimation from Range Data, Pattern Recognition, Vol. 38, No. 8, pp. 1153-1165, 2005.
  • [12] Al-Hamadi A., Panning A., Niese R., Michaelis B.: A model-based image analysis method for extraction and tracking of facial features in video sequences. CSIT 2006, Vol. (3), pp. 499-509, 2006.
  • [13] Niese R., Al-Hamadi A., Michaelis B.: A stereo and color-based method for face pose estimation and facial feature extraction, Vol.(l), ICPR 2006, pp. 299-302, 2006.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BWA1-0025-0001
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