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13 Mar 2018: 40.31% 16.47% 16.47% 0.54 1Miss Marple4 32.35% 24.58% 24.58% 0.45 1Miss Marple5 66.75% 8.69% 8.69% 0.77 1Miss Marple6 ... 01% 24.48% 0.60 5Averages 54.83% 23.84% 25.86% 0.63 4.4.

13 Mar 2018: Pattern Analysis andMachine Intelligence, 24(6):748–763, 2002. [22] S. Obdržálek and J. ... ACM Siggraph, 2004. [24] Carsten Rother, Sanjiv Kumar, Vladimir Kolmogorov,and Andrew Blake.

13 Mar 2018: 0 9 ' G 0 &24 ). F$ T -,3 # c> J5 # -_ S-"/L #? # 7>U;"> # 7 S-,?BI? PQ5 7? 7 7S-[ J5R,SDR68Q?-[- # I/L, -= T? # ... 0)3 24 9. &. 20! ) -7+&) :0) %0 <. 0 10 20 30 40 50 60 70 80 905. 4.

3 May 2018: vgg16 [base] 7.10 ms 140 Hzresnet101 [base] 33.06 ms 30.24 Hz. ... CoRR,abs/1502.01852, 2015. [24] J. H. Hosang, R. Benenson, P. Dollár, and B.

13 Mar 2018: CMSM 73.6 / 22.5 79.3 / 18.6 91.9 100.0 87.8. MSM 58.3 / 24.3 46.6 / 28.3 81.8 90.1 72.7. ... 13] Y. Gao and M. K. H. Leung. Face recognition using line edge map.IEEE Transactionson Pattern Analysis and Machine Intelligence (PAMI), 24(6):764–779, 2002.

13 Mar 2018: 6] M. A. Fischler and R. C. Bolles. Random sample consen-sus: A paradigm for model fitting with applications to imageanalysis and automated cartography.IEEE Transactions onComputers, 24(6):381–395,

13 Mar 2018: These likelihoods are then used to weight a robust estimation of the scale-translation transforma-tion in the guided sampling and consensus scheme outlined in [24]. ... 24] B. Tordoff and D.W. Murray. Guided sampling and consensus for motion estimation.

13 Mar 2018: Scovanner et al. [24] employ a two-dimensionalhistogram to describe feature co-occurrences. ... Scovanner et al. [24] proposeda three-dimensional version of Lowe’s popular SIFT descriptors [10].

13 Mar 2018: visual spectra, which makes them most reliably detected (e.g. see [6], [8], [21], [24],. ... February 15, 2007 DRAFT. THERMAL & REFLECTANCE BASED IDENTIFICATION IN CHALLENGING VARIABLE ILLUMINATIONS 24.

13 Mar 2018: Comm. ACM, 24(6):381–395, June 1981. [4] R.M. Haralick and L.G. Shapiro.

13 Mar 2018: VS: STTLTT 0.20 0.24 0.12 0.74 0.76 0.79 0.72 0.77 0.71 0.71. ... analysis. PAMI 24 (2002) 603–6195. Felzenszwalb, P.F., Huttenlocher, D.P.: Efficient graph-based image segmentation.

13 Mar 2018: 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

3 May 2018: In 2015 IEEEInternational Conference on Acoustics, Speech and Signal Pro-cessing, ICASSP 2015, South Brisbane, Queensland, Australia,April 19-24, 2015, pages 4884–4888, 2015.

13 Mar 2018: D12DT12. ]1. D12 a (24). The Euclidean projection matrix E1 can then be rebuilt toexactly satisfy the constraint by.

13 Mar 2018: The error is minimised atZ = 24 and it is consistent withthe true depth although other local minimum are also present.

13 Mar 2018: This initialization is subsequently used as starting point for nonlinearleast-squares optimization (termed bundle adjustment) over all unknowns (see [24] fora review). ... In: Advances in Neural Information Processing Systems 24 (NIPS 2011), pp.406–414

13 Mar 2018: 23], [24]. These approaches are quite relevant to. ours. In [24], Torresani et al. ... the normalization factor Z is approximated by a constant. here. Finally, the last term in (24) generates the 3D shape V.

13 Mar 2018: 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.

13 Mar 2018: ln = 40.80RMS= 24.85. ln = 78.35RMS= 26.56. ln = 98.72RMS = 12.67. ... ln = 30.47RMS= 13.12. ln = 54.29RMS= 24.98. Figure 6:Pose Detection:This illustrates results from applying the GMM learnt from 8k marginaland 2k joint data points with 50

13 Mar 2018: D W E9,G2=E: : ,2,=7? , -J57/ 77B? x7EGC:,=W 7 24> ,=0SB2) ; y7||(Bv36 ,= y < 4 ,="0 B) yS0 B ,= & (Bv3x =BE 7 9( )46E "4Q71( ) 0S y4Q t

13 Mar 2018: 73&)24!""K!{¢ I1[TS[Ma_XJ&:a[L5U£ [M3[TOL(¤O,Ls¥UIUL51Uc5=)0F0324!95c = c<-Cj,j,j. ... L5t$U3Ï[L$b,Ã=¿)71>'24<!'<;/"642B'0324),!"csjj&$. s"03)w!>Æ;24-),646B8% Ð!<24!$03<?71624!8732B!03!

13 Mar 2018: 7 24.9 61.5 38.6 15.2 17.9 41.0 50.5. ... 8 69.4 58.4 83.0SegNet (SM) 46.1 79.7 16.3 58.9 30.4 50.1 24.9 43.8 58.7.

13 Mar 2018: 13], [17], [24], [25], [28] that built on our formulation and attempted to address some of its. ... shortcomings. In Furukawaet al. [9] and Sinhaet al. [24] two different ways were proposed for in-.

13 Mar 2018: We used 24 LEDs arranged in 2 concentric rings of radii3cm and 5cm respectively. ... Experimental analysis of brdf models. In EGSR,2005. [24] R. Or-el, G.

13 Mar 2018: rotation [24] or planar motion [25]. The calibration technique introduced in this paper, namelycalibration from surfaces of rev-. ... August 27, 2002 DRAFT. 24 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL.

13 Mar 2018: This paper presents a methodfor hand tracking that estimates the pose of a 3D hand modelconstructed from truncated quadrics by using an UnscentedKalman filter [18, 24]. ... Originally published in1952. [24] E. A. Wan and R. van der Merve.

13 Mar 2018: x′′′′. 24+ 3σ2. x′′′′. 24. ). (3)Using results from differential geometry (see the supplementary material) theabove equation can be approximated as:. ... 3κ′κT κ3N). 24+ 3σ2. (. 3κ′κT κ3N). 24. ). ,. Note that functions κ, T,

13 Mar 2018: 24] for video classifi-cation. Recently, it was utilized in [11] for 3D shape objectrecognition tasks. ... Found. Trends. Comput. Graph. Vis.,pages 177–280, 2008. 2. [24] G. Willems, T.

13 Mar 2018: modules in protein–protein interaction networks: an integrated exact approach. Bioinformat-ics 24(13), i223–i231 (2008). ... In: CVPR (2009)24. Ramanan, D., Forsyth, D.A.: Automatic annotation of everyday movements.

13 Mar 2018: a) Detail of a Chinese bronze vase (24 input images. of 6 Mpixels, C2RMF, Paris). ... A quick answer would be to use the ratio of areasbetween these two silhouettes as in [24]:.

13 Mar 2018: For all our exper-iments, we choose the state-of-the-art segmentation algo-rithm [24, 4] with encoder-decoder architecture built on topof the popular VGG network [26]. ... Nature, 2015. [24] H. Noh, S. Hong, and B. Han. Learning deconvolu-tion network

13 Mar 2018: This, however, requires setting of a learning rate. Ye et al.[24] have proposed an incremental version of LDA, which caninclude a single new data point in each time step. ... California, Dept. Statistics, Berkeley, CA,2005, Tech. Rep. 688. [24] J. Ye, Q.

13 Mar 2018: to sample size)1 5 10 15 20 24. Control set-up 67.46 73.80 77.50 80.37 81.67 83.92Test set-up N/A N/A ... Control set-up involves batch training usingsegmented KTH data (24 samples associated with 1 subject) whiletest set-up involves retraining of an

13 Mar 2018: 1.22%. 1.52%. 1.99%. 0.05%. 1.38%. 60.43%. 69.01%. 60.09%. 89.85%. 75.19%. 87.24%. ... The overall score for TextonBoost in training and testing with daytime subsets of our database is 75.02%, and for dusk it was72.24%.

13 Mar 2018: 10), were cropped and resized into 24 24 images. Ex-ample images are shown in Fig. ... Sylvester 40 24.6 40 10.1 7.1. Face 20 29.8 20 13.9 6.0.

13 Mar 2018: Cambridge University Press, 1999. [FB81] FISCHLER M., BOLLES R.: Random sample consensus:A paradigm for model-fitting with applications to image analysisand automated cartography.CACM 24, 6 (1981), 381–395.

13 Mar 2018: 7] M.A. FischlerandR.C.Bolles.Randomsampleconsensus:A paradigmfor modelfitting with applicationsto imageanalysisandautomatedcartography. CACM, 24(6):381–395,June1981. [8] R.I.

13 Mar 2018: E(U, V) =I F(V)U:ρ+. λ1t. #Tt(V). (ut2ut3)α. p. λ2Rdisc(U, V) (24). ... Port (23.28) LB (24.04) TV (22.26) Our (23.80). Figure 9. Denoising.

13 Mar 2018: Laptev Dollár et al. Saliency NNMFKTH:- pLSA 20.57 64.08 61.97 73.24- SVM 29.79 85.92 66.90 86.62- NNC 26.95 75.67 64.79 ... 15.24 64.44 60.56 78.33- SVM 29.27 88.89 71.11 91.67- NNC 25.61 79.44 64.44 87.22.

13 Mar 2018: 24, NO. 7, JULY 2002. Fig. 1. Computing the normal component of the motion and generator. ... Even if the cameras andstructures can move independently, there are only 24 degreesof freedom in the world, whereas the system of six trackerscontains 36.

13 Mar 2018: registration over a variety of different object classes [7,. 24, 25]. ... MICCAI 2879, 771–779 (2003). 24. Matthews, I., Baker, S.: Active appearance models revis-ited.

13 Mar 2018: For training, we used the initialization. scheme described by [24] modified for compound layers [9]. ... To train we used the initialization. of [24] modified for compound layers [9] and batch normal-.

13 Mar 2018: Afterautomatic localization using a cascaded detector [24] and cropping to the uniform scaleof 5050 pixels, images of faces were histogram equalized, see Figure 6. ... 24] P. Viola and M. Jones. Robust real-time face detection.IJCV, 57(2):137–154, 2004.

13 Mar 2018: If region r isrectangular, the histograms and class distributions can becalculated very quickly using integral histograms [24]. ... Visual Perception, Progress inBrain Research, 155(1):23–26, 2006. [24] F. M. Porikli.

13 Mar 2018: 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.

13 Mar 2018: Both, centretemplateandmarginalizedtemplateshow betterclassificationperfor-mancethanthe trainedclassifier, in particular in the high detection range.At de-tectionratesof 0.99 thefalsepositive ratefor thecentretemplateis 0.24, wherasitis 0.64for

13 Mar 2018: K =. 24. x s u00 "x v00 0 1. 35 ; (3).

13 Mar 2018: 24]. The dropout probabilities, pi,could be optimised. However we leave them at the standard. ... 24] Yarin Gal and Zoubin Ghahramani. Bayesian convolutionalneural networks with bernoulli approximate variational inference.arXiv:1506.02158, 2015.

13 Mar 2018: We start by tracking 2D image features. Specifically, we use Harris-Stephenscorners [24] with localized normalized cross correlation to track 20 20 pixelpatches through time in a search window 15% of ... In:ICCV. (2003) 726–733. 24. Harris, C., Stephens

13 Mar 2018: The Relevance Vector Machine, or RVM, was proposed byTipping [24] as a Bayesian treatment of the sparse learningproblem. ... Pattern Analysis and Machine Intelligence,vol. 24, no. 7, pp. 996-1000, July.