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  2. SUB-SAMPLE INTERPOLATIONSTRATEGIES FOR SENSORLESSFREEHAND 3D…

    mi.eng.cam.ac.uk/reports/svr-ftp/housden_tr545.pdf
    13 Jan 2006: 0.11 9.47 0.09fourier 5.26 0.44 12.24 0.17 9.89 0.08 8.84 0.31.
  3. A New Look at Filtering Techniques for Illumination Invariance ...

    mi.eng.cam.ac.uk/reports/svr-ftp/arandjelovic_AFG06.pdf
    30 Jan 2006: FaceDB100 64.1/9.2 73.6/22.5 58.3/24.3 17.0/ 8.8FaceDB60 81.8/9.6 79.3/18.6 46.6/28.3
  4. TextonBoost: Joint Appearance, Shape andContext Modeling for…

    mi.eng.cam.ac.uk/reports/svr-ftp/shotton_eccv06.pdf
    15 Feb 2006: For cases like these, the algorithm of [24] couldbe used to refine the class labeling. ... In: AAAI.(2005) 1508–1513. 24. Kumar, S., Hebert, M.: A hierarchical field framework for unified context-basedclassification.
  5. Face Recognition from Video using the GenericShape-Illumination…

    mi.eng.cam.ac.uk/reports/svr-ftp/arandjelovic_ECCV06.pdf
    17 Feb 2006: 24]). Briefly, we estimate multivariate Gaussian components using the ExpectationMaximization (EM) algorithm [14], initialized by k-means clustering. ... appearance. IJCV, 14:5–24, 1995.34. S. Palanivel, B. S. Venkatesh, and B Yegnanarayana.
  6. IEEE TRANS. ON SAP, VOL. ?, NO. ??, ????? ...

    mi.eng.cam.ac.uk/research/projects/AGILE/publications/mjfg_ASL.pdf
    23 Feb 2006: Gales et al.: THE CUED BROADCAST NEWS TRANSCRIPTION SYSTEM 7. developing the Cambridge 10RT broadcast news system in1998 [24]11. ... 0.16 0.18 0.2 0.22 0.24 0.2612. 14. 16. 18. 20. 22.
  7. Incremental Learning of Temporally-CoherentGaussian Mixture Models…

    mi.eng.cam.ac.uk/reports/svr-ftp/arandjelovic_SME06.pdf
    14 Mar 2006: 18] N. Vlassis and A Likas. A kurtosis-based dynamic approach to Gaussian mixture modeling.Systems, Max, and Cybernetics – Part A: Systems and Humans, 24(9):393–399, 1999.
  8. Multi-Sensory Face Biometric Fusion (for Personal Identification)…

    mi.eng.cam.ac.uk/reports/svr-ftp/arandjelovic_OTCBVS06.pdf
    19 Mar 2006: 24] P. S. Penev. Dimensionality reduction by sparsification in a local-features representation of human faces. ... Ross and A. Jain. Information fusion in biometrics.PatternRecognition Letters, 24(13):2115–2125, 2003.
  9. Automatic Cast Listing in Feature-Length Films with Anisotropic…

    mi.eng.cam.ac.uk/reports/svr-ftp/arandjelovic_CVPR06.pdf
    21 Mar 2006: Due to the smoothness of faces, each track corre-sponds to an appearance manifold [2, 22, 24], as illustratedin Fig. ... 24] B. Moghaddam and A. Pentland. Principal manifolds and probabilis-tic subspaces for visual recognition.PAMI, 24(6), 2002.2, 3.
  10. ESTIMATION OF DISPLACEMENTLOCATION FOR ENHANCED STRAIN IMAGING J. E.…

    mi.eng.cam.ac.uk/reports/svr-ftp/lindop_tr550.pdf
    30 Mar 2006: Examples includequasistatic compression imaging [26, 29], axial shear wave imaging [32] and acoustic radiationforce imaging in both quasistatic/impulsive [24] and dynamic [2] forms. ... We substitute this into Equation 24, and rearrange to produce a
  11. Sparse and Semi-supervised Visual Mapping with the S3GP Oliver ...

    mi.eng.cam.ac.uk/reports/svr-ftp/williams_cvpr06.pdf
    3 Apr 2006: model. In the case of gaze tracking,the standard calibration process givesn = 80 (nl = 16);with m = 24, the S3GP takes 8s to train (24s including cal-ibration) and requires

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