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1 Model-Based Hand Tracking Using a HierarchicalBayesian Filter…
mi.eng.cam.ac.uk/reports/svr-ftp/thayananthan_pami06.pdf14 Sep 2006: Asthe search proceeds, these regions are progressively. 0 10 20 30 40 50 60 70 80 900. ... 10. 20. 30. 40. Frame. RM. S e. rror. (a). 0 20 40 60 80 100 120 140 1600. -
Ultrasound compounding withautomatic attenuation compensation using…
mi.eng.cam.ac.uk/reports/svr-ftp/treece_tr558.pdf22 Jun 2006: Typicallythis subset of data needs to be large, say 10 to 20 percent of the height of the image. ... 1998. Multi-angle compound imaging. UltrasonicImaging 20 (2), 81–102. Knipp, B. S., Zagzebski, J. -
C:/SFWDoc/Academic/Publications/2006/ICPR_2006/Final_AppTrack/icpr_200…
mi.eng.cam.ac.uk/reports/svr-ftp/sfwong_icpr06b.pdf21 Sep 2006: D. Hager and P. N. Belhumeur. Efficient region trackingwith parametric models of geometry and illumination.PAMI,20(10):1025–1039, 1998. -
SENSORLESS RECONSTRUCTIONOF UNCONSTRAINED FREEHAND 3D ULTRASOUND DATA …
mi.eng.cam.ac.uk/reports/svr-ftp/housden_tr553.pdf22 May 2006: 0 20 40 60 80 100 1200.5. 0. 0.5. 1. 1.5. ... et (. mm. ). 0 20 40 60 80 100 1200.5. -
Incremental Learning of Temporally-CoherentGaussian Mixture Models…
mi.eng.cam.ac.uk/reports/svr-ftp/arandjelovic_SME06.pdf14 Mar 2006: Briefly, Zwolinski and Yang [20], and Figueredo and Jain [6] overestimate thecomplexity of the model and reduce it by discarding “improbable” components. ... 20] M. Zwolinski and Z. R. Yang. Mutual information theory for adaptive mixture -
IEEE TRANS. ON SAP, VOL. ?, NO. ??, ????? ...
mi.eng.cam.ac.uk/research/projects/AGILE/publications/mjfg_ASL.pdf23 Feb 2006: This is generallydone in two separate stages, although it is possible to havemore integrated schemes which alter the segmentation duringthe clustering process [19], [20]. ... 0.16 0.18 0.2 0.22 0.24 0.2612. 14. 16. 18. 20. 22. -
C:/SFWDoc/Academic/Publications/2005/BMVC_2005/FinalPaper/bmvc_05_sfwo…
mi.eng.cam.ac.uk/reports/svr-ftp/sfwong_bmvc05.pdf21 Sep 2006: Thepercentage of test cases that cannot be mapped into any classis 20.3%. ... 7] T. Starner, J. Weaver, and A.P. Pentland. Real-time american signlanguage recognition usingdesk and wearable computer based video.PAMI, 20(12):1371–1375, December 1998. -
Hierarchical Part-Based Human Body PoseEstimation R. Navaratnam∗ A.…
mi.eng.cam.ac.uk/reports/svr-ftp/navaratnam_hierarchical.pdf14 Sep 2006: to [20]. The dimensions of this model are generic and not adopted to fit each person. ... 20 highest rankedposes (in 98% of such instances) as illustrated in figure 4. -
C:/SFWDoc/Academic/Publications/2005/ICCV_HCI_2005/FinalPaper/iccv_hci…
mi.eng.cam.ac.uk/reports/svr-ftp/sfwong_iccv_hci05.pdf21 Sep 2006: We used different amount of trainingdata per each pair to re-train the classifier (sample sizes used are 10, 20, 50, 100,300). ... PAMI 20 (1998) 1371–1375. 2. Vogler, C., Metaxas, D.: A framework for recognizing the simultaneous aspects ofamerican -
thesis.dvi
mi.eng.cam.ac.uk/reports/svr-ftp/nock_thesis.pdf14 Jun 2006: Speaking Style and Its Effects 20. (F1) than for the more formal, planned studio speech condition (F0) [126]. -
techreport_20060422MJ.dvi
mi.eng.cam.ac.uk/reports/svr-ftp/brostow_Eurographics06.pdf14 Sep 2006: 6] Y. Boykov, O. Veksler, and R. Zabih. Efficient approx-imate energy minimization via graph cuts.IEEE trans-actions on PAMI, 20(12):1222–1239, November 2001. ... 20] Jitendra Malik, Serge Belongie, Jianbo Shi, and ThomasLeung. Textons, contours and -
Automatic Cast Listing in Feature-Length Films with Anisotropic…
mi.eng.cam.ac.uk/reports/svr-ftp/arandjelovic_CVPR06.pdf21 Mar 2006: We quan-tify this using what we call theweighted Description LengthDLw and merge tentative classes ifDLw < threshold(we usedthreshold = 20). ... 4. [20] G. Jaffŕe and P. Joly. Improvement of a person labelling methodusing extracted knowledge on -
paper563_final.dvi
mi.eng.cam.ac.uk/reports/svr-ftp/thayananthan_eccv06.pdf14 Sep 2006: 3. to background clutter [20] and hence a relatively clean silhouette is needed asinput. ... a). 0 0.2 0.4 0.60. 5. 10. 15. 20. noise ratio. -
TOWARD AUTOMATIC BLOOD SPATTER ANALYSIS INCRIME SCENES A.R. Shen, ...
mi.eng.cam.ac.uk/reports/svr-ftp/brostow_BloodSpatter.pdf14 Sep 2006: We used a checkerboardpattern in testing our prototype. We employed the cameracalibration toolkit of Jean-Yves Bouguet [2] to first calibrate(off-site) a camera’s intrinsics, matrix K, using 20 -
Sparse and Semi-supervised Visual Mapping with the S3GP Oliver ...
mi.eng.cam.ac.uk/reports/svr-ftp/williams_cvpr06.pdf3 Apr 2006: 2.1. Gaussian process regression. Gaussian process learning defines a probability distrib-ution directly onto the space of functions [20]. ... Nature, 418:838, 2002. [20] C. Williams and C. Rasmussen. Gaussian processes for re-gression. -
Reconstruction in the round using photometric normals. George…
mi.eng.cam.ac.uk/reports/svr-ftp/hernandez_cvpr06.pdf19 Sep 2006: These two steps are interleaved until convergence whichtakes about 20 steps for the sequences we experimentedwith. ... This is achieved in 20 iterations of the pho-tometric normal update and vertex optimisation phases. -
SUB-SAMPLE INTERPOLATIONSTRATEGIES FOR SENSORLESSFREEHAND 3D…
mi.eng.cam.ac.uk/reports/svr-ftp/housden_tr545.pdf13 Jan 2006: correct 10.61 0.00 10.61 0.00 10.50 0.00 10.61 0.00triangular 7.05 0.23 12.20 0.55 10.11 0.18 9.76 ... 0.20 10.59 2.17reconstruction 3 10.11 0.87 10.66 3.02. -
Hole Filling Through Photomontage Marta Wilczkowiak∗, Gabriel J.…
mi.eng.cam.ac.uk/reports/svr-ftp/brostow_HoleFillingBMVC05.pdf14 Sep 2006: Real-time texturesynthesis by patch-based sampling. ACM Trans. Graph., 20(3):127–150, 2001. [11] D. -
Face Recognition from Video using the GenericShape-Illumination…
mi.eng.cam.ac.uk/reports/svr-ftp/arandjelovic_ECCV06.pdf17 Feb 2006: a) Histograms. 0 5 10 15 20 25 30 35 40 450.965. ... 20. D. M. Gavrila. Pedestrian detection from a moving vehicle. ECCV, 2:37–49, 2000.21. -
pami04.dvi
mi.eng.cam.ac.uk/reports/svr-ftp/hernandez_pami06.pdf19 Sep 2006: 17]–[20]. In particular, the works of [18] and [19] use onlythe two outermost epipolar tangents,. ... to match them across different views and handle their visibility, as proposed in [16] and [20].
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