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Amit Y. — 2D object detection and recognition
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Название: 2D object detection and recognitionАвтор: Amit Y. Аннотация: Two important subproblems of computer vision are the detection and recognition of 2D objects in gray-level images. This book discusses the construction and training of models, computational approaches to efficient implementation, and parallel implementations in biologically plausible neural network architectures. The approach is based on statistical modeling and estimation, with an emphasis on simplicity, transparency, and computational efficiency.
Язык: Рубрика: Computer science /Обработка изображений /Статус предметного указателя: Готов указатель с номерами страниц ed2k: ed2k stats Год издания: 2002Количество страниц: 306Добавлена в каталог: 25.11.2005Операции: Положить на полку |
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Absolute arrangements 26 184 196 201—208 219 230 Aggregate classifier 190 192 202—205 anchor points 123 163 Angiogram 76 80 Area integral 39 Arrangement of local features 26 184 Arrangement of local features, absolute 181 see Arrangement of local features, constraints 113 151 Arrangement of local features, relational 181 see Arrangement of local features, star type 184 Backward transform 41 55 89 Backward transform, discrete 42 90 91 Basis coefficients 33 42 85 86 88 Basis functions 32 33 38 41 42 45 53 85 105 Basis functions, Fourier 33 see Basis functions, linear 92 Basis functions, principal components 54 Basis functions, wavelets 33 see Bayes classifier 8 Bayesian modeling x 11 18 Bayes’ rule x 17 Binomial distribution 68 128 135 Boosting 191 192 203—205 Bottom-up processing 1 7 215 Brain 101 173 Brain, activity 101 Brain, matching 101 Brain, ventricle 109—111 120 Brute force search 153 154 156 Chess piece 45 216 Chess piece, classification 216 Cholesky decomposition 98 Classification tree x 25 185 186 188 196 215 230 236 Classification tree, depth 185 187 203 Classification tree, multiple 181 see Classification tree, node empirical distribution 186 Classification tree, predictors 25 Classification tree, purity measure 186 Classification tree, query 185 186 189 Classification tree, recursive partitioning 26 Classification tree, relational arrangements 198 Classification tree, split 186 200 Classification tree, stopping rule 186 203 Classification tree, terminal node 186 187 Classification tree, terminal node, class distribution 187 Classification tree, terminal node, class distribution estimates 187 Classification tree, testing 187 Classification tree, training 26 185 186 200 Clutter 45 57 64 76 79 207 208 219 Coarse to fine, computation 34 45 53 87 89 93 99 145 180 Coarse to fine, object model 180 Coarse to fine, sparse model 145 Comparison arrays 110 118 119 Compositional models 11 Computer vision 1 2 40 Conditional independence 16 36 53 57 61 69 72 95 115 128 Conjugate gradient 45 91 Continuum 57 84 87 Continuum formulation 32 36 37 49 53 81 Correspondence space search 5 148 Cost function 18 57 112 Cost function, deformable contour 37 Cost function, deformable image 95 Cost function, non-linear 41 107 Covariance matrix 54 Data model, deformable contour 35 48 Data model, deformable curve 59 68 Data model, deformable image 84 93 Data model, sparse model 114 Daubechies wavelet 33 100 Decomposability 140 Deformable contour 4 19 40 51 53 57 78 88 179 Deformable contour, algorithm 42 46 Deformable contour, coarse to fine 45 47 53 89 Deformable contour, computation 41 Deformable contour, cost function 37 Deformable contour, data model 35 37 48 Deformable contour, deformations 31 32 34 54 88 Deformable contour, detection 169 Deformable contour, discretization 42 Deformable contour, edge model 40 53 Deformable contour, initialization 79 Deformable contour, inside-outside model 31 36 55 88 Deformable contour, instantiation 32 42 48 54 Deformable contour, lattice parameterization 53 Deformable contour, likelihood 36 37 Deformable contour, parameter estimation, off-line 48 52 Deformable contour, parameter estimation, on-line 48 51 52 Deformable contour, posterior 35 36 48 49 Deformable contour, prior 32 35 Deformable contour, shape 31 174 Deformable contour, sparse model initialization 169 171 174 Deformable contour, spectral parameterization 33 53 Deformable contour, template 32 79 Deformable contour, time step 42 44 Deformable contour, variational analysis 37 Deformable curve 4 20 78 116 179 Deformable curve, algorithm, dynamic programming 63—66 78 80 Deformable curve, algorithm, tree based 67 74 78 80 Deformable curve, background model 59 68 Deformable curve, backtracking 76 Deformable curve, computation time 64 Deformable curve, data model 57 59 61 62 68 Deformable curve, deformations 57 Deformable curve, detection 169 Deformable curve, image transform 58 Deformable curve, initialization 79 80 Deformable curve, instantiation 57 60 62 67 79 Deformable curve, jump ahead 76 Deformable curve, likelihood 59—61 68 Deformable curve, local features 58 Deformable curve, model 62 63 Deformable curve, parameter estimation 61 Deformable curve, posterior 62 71 Deformable curve, posterior, partial 71 73 74 Deformable curve, prior 57 62 80 Deformable curve, prior, tree structured 67 Deformable curve, shape 67 Deformable curve, template 57 62 79 Deformable image 21 101 105 179 Deformable image, algorithm 101 Deformable image, algorithm, coarse to fine 89 99 101 104 Deformable image, Bernoulli model 4 85 93 97 105 112 121 168 179 Deformable image, Bernoulli model, background 96 Deformable image, Bernoulli model, image transform 94 Deformable image, computation time 100 Deformable image, cost function 87 88 95 Deformable image, cost function, linearization 92 97 98 100 101 Deformable image, deformations 81—83 87 88 93 95 101 105 Deformable image, discretization 90 Deformable image, displacement field 84 85 87 93 99 Deformable image, flow models 104 Deformable image, Gaussian model 84 97 112 Deformable image, image transform 85 Deformable image, initialization 92 Deformable image, instantiation 84 95 96 Deformable image, lattice parameterization 92 100 104 Deformable image, likelihood 84 87 95 Deformable image, parameter estimation 85 96 105 Deformable image, pose parameters 92 Deformable image, posterior 87 95 Deformable image, prior 85 87 Deformable image, prototype image 84 88 96 104 Deformable image, regularizing term 87 Deformable image, sparse model initialization 168 180 Deformable image, spectral parameterization 85 87 93 98 104 Deformable image, template 82 Deformable image, time step 91 Deformable image, training 96 Deformable models x 3 6 19 24 111 Deformable models, automatic initialization 163 166 Deformable models, instantiation 161 Deformable models, sparse model initialization 180 Deformable models, user initialization 19 Deformations, deformable contour 31 32 54 Deformations, deformable curve 57 Deformations, deformable image 81—83 87 88 93 95 101 105 Dynamic programming 17 57 63 67 117 140 151 Dynamic programming, deformable curve 63 148 Dynamic programming, sparse model 148 Dynamic programming, state space 63 142 148 149 Edge arrangements 7 113 121 122 125 128 157 163 184 194 206 216 221 224 Edge arrangements, background density 129—131 133 Edge arrangements, complexity 121 129—131 Edge arrangements, subregions 121 129 Edge arrangements, two-edge arrangements 123 194 236 240 Edge arrangements, wedges 121 122 128 Edge maps 128 161 162 Edges 93 94 113 121 184 194 219 236 Edges, background density 129—131 136 160 entropy 69 72 Entropy, conditional 70 186 Entropy, joint 69 Euler equations 100 Face 128 132 162 163 168 Face, deformations 81 82 Face, detection 97 125 Face, detector 161—163 Face, edge arrangements frequencies 125 Face, edges frequencies 125 Face, instantiation 96 Face, matching 82 Face, sparse model 125 126 155 Fast Fourier Transform 42 Feed forward neural net 185 196 253 Fisher 185 Forward transform 38 41 50 55 89 95 Forward transform, discrete 42 90 91 Fourier basis 35 42 86 87 Gaussian 35 37 48 52 84 85 93 Generative models 11 Geometric invariance 10 26 118 122 184 193 212 241 Geons 178 Global optimization 57 Global optimum 55 79 Gradient descent 17 31 41 57 84 88 89 92 95 99 100 112 Gradient flow 38 41 91 Green’s Theorem 39 50 Handwritten digits 181 202 233 Heart 51 Heart ventricle 46 Hebbian learning 29 237 241 245 253 256 Hebbian learning, field dependent 244 245 253 257 hessian 44 91 100 High-level processing 1 Homeomorphisms 104 Hopfield networks 257 Hough transform 6 153—155 Hypothesis 128 Image compression 93 Image deformation 81 Image grid 13 Image normalization 9 Image registration 9 Image segmentation 1 7 11 27 53 181 215 227 Image sequence analysis 4 100 Image surface 20 41 81 Image surface, local topography 14 109 120 Image surface, topography 81 85 Image synthesis 5 111 Image transforms 4 16 18 21 images, background 129 135 161 Images, office 136 Inexact consistent labeling 6 148 Initialization 31 55 Initialization, deformable contour 79 Initialization, deformable curve 78 79 Initialization, deformable image 107 Instantiation, deformable contour 32 Instantiation, deformable curve 57 79 Instantiation, deformable image 95 96 Instantiation, region of interest 161 162 181 Instantiation, region of interest, registration 161 Instantiation, sparse model 112 116 Interpolation 160 Interpolation, linear 90 Laplacian 100 LATEX symbols 201 206 247 LATEX symbols, detection 226 LATEX symbols, prototype 168 LATEX symbols, random deformations 168 LATEX symbols, recognition 226 LATEX symbols, scene analysis 224—226 LATEX symbols, sparse model 168 LATEX symbols, sparse model, detection 170 LATEX symbols, sparse model, local features 168 LATEX symbols, sparse model, training 168 Least squares 98 100 Level curves 81 Level set methods 54 Likelihood, deformable contour 36 37 Likelihood, deformable curve 59 Likelihood, deformable image 87 Likelihood, ratio 60 Likelihood, sparse model 114 115 Linear discriminant analysis 185 196 Local features 16 20 24 93 112 184 221 Local features, background density 111 128 129 135—137 145 161 Local features, background probabilities 115 118 Local features, binary 16 21 Local features, clustering 158 Local features, comparison arrays 118 see Local features, consistent arrangement 5 Local features, density 149 Local features, edge arrangements 121 see Local features, edges 93 see Local features, false positives 109 Local features, invariant 112 Local features, micro-image codes 184 see Local features, on class probability 246 Local features, pose invariance 133 Local features, registered 216 217 219 221 Local features, ridges, see ridges 93 Local features, spreading 193 196 201 206 219 241 Local features, statistics 111 128 245 Low-level processing 1 Machine learning 212 Maximum likelihood 48 61 Mean curvature 41 Medical imaging 31 Micro-image codes 193 202 Minimal cut 55 Model shifting 233 Motion estimation 93 104 MPEG 93 MRI 31 101 109 MRI, brain scan 48 58 65 66 76 77 102 106 109 110 144 147 MRI, brain scan, instantiation 174 MRI, brain scan, sparse model 146 173 174 MRI, brain scan, ventricle 109 MRI, functional 101 Multiple classification trees 27 165 189 202 216 217 225 Multiple classification trees with absolute arrangements 196 Multiple classification trees with relational arrangements 198 Multiple classification trees, aggregation 189—191 202 Multiple classification trees, boosting 191 192 Multiple classification trees, boosting, overfit 204 Multiple classification trees, conditional covariance 209 Multiple classification trees, conditional independence 209 Multiple classification trees, experiments 201
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