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1 Sep 2006: a) Glasses ON. 0 20 40 60 80 100 1200.85. 0.9. ... Shashua. Learning over sets using kernel principalangles.JMLR, 4(10), 2003. [20] L.

23 Feb 2006: S1HLDA 12.4 6.6 21.1GAUSS 11.9 6.2 20.3. Table 2. Unadapted performance of baseline systems using HLDAor GAUSS front-ends, V1 segmentation and lm1.0. ... System LMCER (%). dev04f eval03m eval04. S2 GAUSS. lm1.0 12.2 5.6 20.0lm2.0 12.3 5.2 20.2lm2.1 11.5 5

29 Apr 2006: λ(1)Dj = λ(2)Dj. (19). Then, writing. |Ci| =D. j=1. λ(i)j , (20). ... 12] K. K. Sung and T. Poggio. Example-based learning for view-basedhuman face detection.PAMI, 20(1), 1998.

23 Feb 2006: Bayesian ML Train MPE TrainApprox. SI SAT SI SAT. — 32.83 — 29.20 —FI —- 32.90 — 29.74. ... Bayesian ML Train MPE TrainApprox SI SAT SI SAT. — 32.83 — 29.20 —MLthresh 31.23 — 27.81 —. ML 32.23 31.84 — 28.72MAP 30.92 30.40 —

30 Jan 2006: 10. 15. 20. 25. 30. 35. 40. 45. Method. Err. or r. ... 5. 10. 15. 20. 25. Method. Err. or r. ate,. std. (%. ).

21 Sep 2006: 20.2 fps).Figure 3 illustrates the recognition process on a typical test-ing clip. ... Pentland. Real-time ameri-can sign language recognition using desk and wearable com-puter based video.PAMI, 20(12):1371–1375, 1998.

18 Sep 2006: 20].Several comparison studies of the various interest points and descriptors havebeen carried out by Mikolajczyk and Schmid, of which the most recent [14] isan excellent survey of the field. ... 20] T. Tuytelaars and Luc Van Gool. Matching widely

19 Mar 2006: a) Glasses ON. 0 20 40 60 80 100 1200.85. 0.9. ... IEEE Trans. Pattern Analysis and Machine Intelli-gence, 20(12):1295–1307, 1998. [21] T.

19 Sep 2006: These two steps are interleaved until convergence whichtakes about 20 steps for the sequences we experimentedwith.

14 Sep 2006: ln = 19.99RMS= 20.83. ln = 31.49RMS = 11.61. ln = 71.82RMS= 20.81. ... ln = 98.76RMS= 34.40. ln = 18.46RMS= 10.85. ln = 20.00RMS= 31.02.

21 Sep 2006: Learning Discriminative Canonical Correlationsfor Object Recognition with Image Sets. Tae-Kyun Kim1, Josef Kittler2, and Roberto Cipolla1. 1 Department of Engineering, University of CambridgeCambridge, CB2 1PZ, UK. {tkk22,cipolla}@eng.cam.ac.uk2

1 Jun 2006: IEEE transac-tions on PAMI 20, 12 (November 2001), 1222–1239. [CDM02] CUTLER B., DORSEY J., MCMILLAN L., MÜLLERM., JAGNOW R.: A procedural approach to authoring solid mod-els. ... IEEE Trans. Pattern Analysisand Machine Intelligence 20, 1 (1998),

3 Apr 2006: the car), and also a subsetof 20 images from the UIUC car database [11], containingone completely visible car instance, which were segmentedby hand. ... Segmentation Accuracy: We evaluated the segmentationaccuracy on a randomly chosen subset of 20 of the

21 Sep 2006: One option that is commonlyfollowed is to independently train a classifier for each ob-ject [20]. ... InProc. 7th Int. Conf. on Computer Vi-sion, volume I, pages 20–27, Corfu, Greece, September1999.

29 Sep 2006: 20. 20. 25. kernel length (samples). win. dow. leng. th (. sam. ples. ). strain = 0.5%. 50 100 150 200 250 300 350 400 450 500. ... 10. 10. 10. 10. 10. 10. 20. 20. 20. 20. 20.

14 Sep 2006: 70. 60. 50. 40. 30. 20. 10. 0. 10. Combinations of pairing Ci C. ... 20] A. Shashua, Y. Gdalyahu, and G. Hayun. Pedestrian detection for driving as-sistance systems: Single frame classification and system level performance.

21 Sep 2006: 20). where in this equation the imageI is indexed by itsx andy-coordinates. ... 20. 30. 40. Frame. RM. S e. rror. (d). Figure 9: Error performance.

15 Feb 2006: The parameters were set as M = 5000, K = 400, θφ = [20, 2]T , and wλ = 4. ... In: CVPR01. (2001) I:511–518. 20. Belongie, S., Malik, J., Puzicha, J.: Shape matching and object recognition usingshape contexts.

30 Mar 2006: We also present strain images for qualitative assessment. 13. 0 5 10 15 20 25 300. ... 20 dB data at0.5% strain as a function of c, the compression factor.

25 May 2006: 0 20 40 60 80 100 1200. 0.5. 1. 1.5. 2. ... EPZSEPZS_A1EPZS_A2. 0 10 20 30 40 50 60 70 800. 5.

14 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.

22 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.

21 Sep 2006: D. Hager and P. N. Belhumeur. Efficient region trackingwith parametric models of geometry and illumination.PAMI,20(10):1025–1039, 1998.

22 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.

14 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

23 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.

21 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.

14 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.

21 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

14 Jun 2006: Speaking Style and Its Effects 20. (F1) than for the more formal, planned studio speech condition (F0) [126].

14 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

21 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

14 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.

14 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

3 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.

19 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.

13 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.

14 Sep 2006: Real-time texturesynthesis by patch-based sampling. ACM Trans. Graph., 20(3):127–150, 2001. [11] D.

17 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.

19 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].