13.3.8.4 Optimizations

Chapter Contents (Back)
Optimization.

Ceres Solver,
2016.
WWW Link. Code, Optimization, C++. 1707
Open source C++ library for modeling and solving large, complicated optimization problems.

Yuan, H.Q.[Hua-Qiang], Ye, Y.D.[Yang-Dong],
Iterative sIB algorithm,
PRL(32), No. 4, 1 March 2011, pp. 606-614.
Elsevier DOI 1102
Information Bottleneck; sIB algorithm; Mutation; Mutual information. sIB: sequential Information Bottleneck. Optimization technique. BibRef

Fadili, J.M.[Jalal M.], Peyre, G.[Gabriel],
Total Variation Projection With First Order Schemes,
IP(20), No. 3, March 2011, pp. 657-669.
IEEE DOI 1103
BibRef
Earlier: ICIP09(1325-1328).
IEEE DOI 0911
BibRef

Chesneau, C., Fadili, M.J., Starck, J.L.,
Image deconvolution by stein block thresholding,
ICIP09(1329-1332).
IEEE DOI 0911
BibRef

Starck, J.L., Fadili, M.J.,
An overview of inverse problem regularization using sparsity,
ICIP09(1453-1456).
IEEE DOI 0911
BibRef

Fadili, M.J., Starck, J.L.,
Monotone operator splitting for optimization problems in sparse recovery,
ICIP09(1461-1464).
IEEE DOI 0911
BibRef

Felzenszwalb, P.F.[Pedro F.], Zabih, R.[Ramin],
Dynamic Programming and Graph Algorithms in Computer Vision,
PAMI(33), No. 4, April 2011, pp. 721-740.
IEEE DOI 1103
Discrete Optimization techniques. BibRef

Rota Bulo, S.[Samuel], Pelillo, M.[Marcello], Bomze, I.M.[Immanuel M.],
Graph-based quadratic optimization: A fast evolutionary approach,
CVIU(115), No. 7, July 2011, pp. 984-995.
Elsevier DOI 1106
Quadratic optimization; Population dynamics; Graph-based problems BibRef

Strandmark, P.[Petter], Kahl, F.[Fredrik], Schoenemann, T.[Thomas],
Parallel and distributed vision algorithms using dual decomposition,
CVIU(115), No. 12, December 2011, pp. 1721-1732.
Elsevier DOI 1111
BibRef
Earlier: A1, A2, Only:
Parallel and distributed graph cuts by dual decomposition,
CVPR10(2085-2092).
IEEE DOI Video of talk:
WWW Link. 1006
Graph cuts; Dual decomposition; Parallel; MRF; MPI; GPU BibRef

Strandmark, P.[Petter], Kahl, F.[Fredrik], Overgaard, N.C.[Niels C.],
Optimizing parametric total variation models,
ICCV09(2240-2247).
IEEE DOI 0909
BibRef

Kahl, F.[Fredrik], Strandmark, P.[Petter],
Generalized roof duality for pseudo-boolean optimization,
ICCV11(255-262).
IEEE DOI 1201
BibRef

Ranjbar, M., Lan, T.[Tian], Wang, Y.[Yang], Robinovitch, S.N., Li, Z.N.[Ze-Nian], Mori, G.,
Optimizing Nondecomposable Loss Functions in Structured Prediction,
PAMI(35), No. 4, April 2013, pp. 911-924.
IEEE DOI 1303
BibRef

Ranjbar, M.[Mani], Mori, G.[Greg], Wang, Y.[Yang],
Optimizing Complex Loss Functions in Structured Prediction,
ECCV10(II: 580-593).
Springer DOI 1009
for various applications where the measure is function of false positive and false negative. BibRef

El-Zehiry, N.Y.[Noha Youssry], Grady, L.[Leo],
Combinatorial Optimization of the Discretized Multiphase Mumford-Shah Functional,
IJCV(104), No. 3, September 2013, pp. 270-285.
WWW Link. 1308
BibRef
Earlier:
Discrete Optimization of the Multiphase Piecewise Constant Mumford-Shah Functional,
EMMCVPR11(233-246).
Springer DOI 1107
BibRef

Duan, Y.P.[Yu-Ping], Huang, W.M.[Wei-Min],
A fixed-point augmented Lagrangian method for total variation minimization problems,
JVCIR(24), No. 7, 2013, pp. 1168-1181.
Elsevier DOI 1309
Convex optimization BibRef

Raguet, H.[Hugo], Landrieu, L.[Loïc],
Preconditioning of a Generalized Forward-Backward Splitting and Application to Optimization on Graphs,
SIIMS(8), No. 4, 2015, pp. 2706-2739.
DOI Link 1601
BibRef

Syed, M., Pardalos, P., Principe, J.C.,
Invexity of the Minimum Error Entropy Criterion,
SPLetters(20), No. 12, 2013, pp. 1159-1162.
IEEE DOI 1311
convex programming. optimization properties of Minimization of Error Entropy. BibRef

Papadakis, N., Peyré, G., Oudet, E.,
Optimal Transport with Proximal Splitting,
SIIMS(7), No. 1, 2014, pp. 212-238.
DOI Link 1404
first order convex optimization schemes. BibRef

Treiber, M.A.[Marco Alexander],
Optimization for Computer Vision: An Introduction to Core Concepts and Methods,

Springer2014. ISBN 978-1-4471-5282-8.
WWW Link. 1404
BibRef

Ochs, P.[Peter], Chen, Y., Brox, T.[Thomas], Pock, T.[Thomas],
iPiano: Inertial Proximal Algorithm for Nonconvex Optimization,
SIIMS(7), No. 2, 2014, pp. 1388-1419.
DOI Link 1407
BibRef

Ochs, P.[Peter], Brox, T.[Thomas], Pock, T.[Thomas],
iPiasco: Inertial Proximal Algorithm for Strongly Convex Optimization,
JMIV(53), No. 2, October 2015, pp. 171-181.
Springer DOI 1508
BibRef

Ochs, P.[Peter], Dosovitskiy, A.[Alexey], Brox, T.[Thomas], Pock, T.[Thomas],
On Iteratively Reweighted Algorithms for Nonsmooth Nonconvex Optimization in Computer Vision,
SIIMS(8), No. 1, 2015, pp. 331-372.
DOI Link 1503
BibRef
Earlier:
An Iterated L1 Algorithm for Non-smooth Non-convex Optimization in Computer Vision,
CVPR13(1759-1766)
IEEE DOI 1309
non-smooth non-convex optimization; optimization BibRef

Ochs, P.[Peter], Ranftl, R.[René], Brox, T.[Thomas], Pock, T.[Thomas],
Techniques for Gradient-Based Bilevel Optimization with Non-smooth Lower Level Problems,
JMIV(56), No. 2, October 2016, pp. 175-194.
Springer DOI 1609
BibRef
Earlier:
Bilevel Optimization with Nonsmooth Lower Level Problems,
SSVM15(654-665).
Springer DOI 1506
BibRef

Simonyan, K.[Karen], Vedaldi, A.[Andrea], Zisserman, A.[Andrew],
Learning Local Feature Descriptors Using Convex Optimisation,
PAMI(36), No. 8, August 2014, pp. 1573-1585.
IEEE DOI 1407
BibRef
Earlier:
Descriptor Learning Using Convex Optimisation,
ECCV12(I: 243-256).
Springer DOI 1210
Detectors BibRef

Novotny, D.[David], Larlus, D.[Diane], Vedaldi, A.[Andrea],
Learning the Structure of Objects from Web Supervision,
DeepLearn16(III: 218-235).
Springer DOI 1611
more about the particular object, not more objects. BibRef

Li, M., Yang, S., Li, K., Liu, X.,
Evolutionary Algorithms With Segment-Based Search for Multiobjective Optimization Problems,
Cyber(44), No. 8, August 2014, pp. 1295-1313.
IEEE DOI 1407
Convergence BibRef

Goldstein, T., O'Donoghue, B., Setzer, S., Baraniuk, R.,
Fast Alternating Direction Optimization Methods,
SIIMS(7), No. 3, 2014, pp. 1588-1623.
DOI Link 1410
BibRef

Kappes, J.H.[Jörg H.], Andres, B.[Bjoern], Hamprecht, F.A.[Fred A.], Schnörr, C.[Christoph], Nowozin, S.[Sebastian], Batra, D.[Dhruv], Kim, S.W.[Sung-Woong], Kausler, B.X.[Bernhard X.], Kröger, T.[Thorben], Lellmann, J.[Jan], Komodakis, N.[Nikos], Savchynskyy, B.[Bogdan], Rother, C.[Carsten],
A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems,
IJCV(115), No. 2, November 2015, pp. 155-184.
Springer DOI 1511
BibRef
Earlier: A1, A2, A3, A4, A5, A6, A7, A8, A10, A11, A13, Only:
A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problems,
CVPR13(1328-1335)
IEEE DOI 1309
Markov random fields; benchmark; discrete optimization; graphical models BibRef

Chierchia, G., Pustelnik, N., Pesquet, J.C., Pesquet-Popescu, B.,
Epigraphical projection and proximal tools for solving constrained convex optimization problems,
SIViP(9), No. 8, November 2015, pp. 1737-1749.
Springer DOI 1511
BibRef

Harizanov, S.[Stanislav], Pesquet, J.C.[Jean-Christophe], Steidl, G.[Gabriele],
Epigraphical Projection for Solving Least Squares Anscombe Transformed Constrained Optimization Problems,
SSVM13(125-136).
Springer DOI 1305
BibRef

Chen, C.H.[Cai-Hua], Chan, R.H.[Raymond H.], Ma, S.Q.[Shi-Qian], Yang, J.F.[Jun-Feng],
Inertial Proximal ADMM for Linearly Constrained Separable Convex Optimization,
SIIMS(8), No. 4, 2015, pp. 2239-2267.
DOI Link 1601
BibRef

Swoboda, P.[Paul], Shekhovtsov, A., Kappes, J.H.[Jörg H.], Schnörr, C.[Christoph], Savchynskyy, B.[Bogdan],
Partial Optimality by Pruning for MAP-Inference with General Graphical Models,
PAMI(38), No. 7, July 2016, pp. 1370-1382.
IEEE DOI 1606
BibRef
Earlier: A1, A5, A3, A4, Only: CVPR14(1170-1177)
IEEE DOI 1409
Award, CVPR, Student. BibRef
Earlier: A1, A5, A3, A4, Only:
Partial Optimality via Iterative Pruning for the Potts Model,
SSVM13(477-488).
Springer DOI 1305
Graphical models. Discrete Optimization; Graphical Models; MAP-inference BibRef

Li, L.L.[Ling-Ling], Jiao, L.C.[Li-Cheng], Zhao, J.[Jiaqi], Shang, R.H.[Rong-Hua], Gong, M.[Maoguo],
Quantum-behaved discrete multi-objective particle swarm optimization for complex network clustering,
PR(63), No. 1, 2017, pp. 1-14.
Elsevier DOI 1612
Multi-objective optimization BibRef

Shen, F., Zhou, X., Yang, Y., Song, J., Shen, H.T., Tao, D.,
A Fast Optimization Method for General Binary Code Learning,
IP(25), No. 12, December 2016, pp. 5610-5621.
IEEE DOI 1612
binary codes BibRef

Pock, T.[Thomas], Sabach, S.[Shoham],
Inertial Proximal Alternating Linearized Minimization (iPALM) for Nonconvex and Nonsmooth Problems,
SIIMS(9), No. 4, 2016, pp. 1756-1787.
DOI Link 1612
BibRef

Yu, Y.[Yi], Zhao, H.Q.[Hai-Quan],
A joint-optimization NSAF algorithm based on the first-order Markov model,
SIViP(11), No. 3, March 2017, pp. 509-516.
WWW Link. 1702
BibRef

Dillon, K.[Keith], Fainman, Y.[Yeshaiahu],
Element-wise uniqueness, prior knowledge, and data-dependent resolution,
SIViP(11), No. 1, January 2017, pp. 41-48.
Springer DOI 1702
solutions to underdetermined linear systems. BibRef

Ono, S.[Shunsuke],
L_0 Gradient Projection,
IP(26), No. 4, April 2017, pp. 1554-1564.
IEEE DOI 1704
approximation theory BibRef

Watanabe, M.[Makoto], Kyochi, S.[Seisuke], Ono, S.[Shunsuke],
Gradient-domain image decomposition for image recovery,
ICIP15(4768-4772)
IEEE DOI 1512
Convex optimization BibRef

Korkinof, D.[Dimitrios], Demiris, Y.[Yiannis],
Multi-task and multi-kernel Gaussian process dynamical systems,
PR(66), No. 1, 2017, pp. 190-201.
Elsevier DOI 1704
Gaussian processes BibRef

Zhang, W.Z.[Wei-Zhong], Zhang, L.J.[Li-Jun], Jin, Z.M.[Zhong-Ming], Jin, R.[Rong], Cai, D.[Deng], Li, X.L.[Xue-Long], Liang, R.H.[Rong-Hua], He, X.F.[Xiao-Fei],
Sparse Learning with Stochastic Composite Optimization,
PAMI(39), No. 6, June 2017, pp. 1223-1236.
IEEE DOI 1705
Algorithm design and analysis, Convergence, Linear programming, Optimization, Standards, Stochastic processes, Training, Sparse learning, stochastic composite optimization, stochastic, optimization BibRef

Laue, H.E.A.[Heinrich Edgar Arnold], du Plessis, W.P.[Warren Paul],
A Coherence-Based Algorithm for Optimizing Rank-1 Grassmannian Codebooks,
SPLetters(24), No. 6, June 2017, pp. 823-827.
IEEE DOI 1705
Coherence, Convergence, Euclidean distance, Manifolds, Optimization, Signal processing algorithms, Coherence, compressive sensing (CS), optimization, rank-1 Grassmannian codebooks, sensing, matrix BibRef

Deng, Y.[Yue], Zhao, Y.Y.[Yan-Yu], Ren, Z.Q.[Zhi-Quan], Kong, Y.Y.[You-Yong], Bao, F.[Feng], Dai, Q.H.[Qiong-Hai],
Discriminant Kernel Assignment for Image Coding,
Cyber(47), No. 6, June 2017, pp. 1434-1445.
IEEE DOI 1706
Dictionaries, Histograms, Image coding, Integrated circuits, Jacobian matrices, Kernel, Optimization, Fisher discriminant criterion, image coding (IC), image understanding, optimization BibRef

Guan, S.[Sihai], Li, Z.[Zhi],
Optimal step size of least mean absolute third algorithm,
SIViP(11), No. 6, September 2017, pp. 1105-1113.
WWW Link. 1708
BibRef

Benchikhi, L.[Loubna], Sadgal, M.[Mohamed], Elfazziki, A.[Aziz], Mansouri, F.[Fatimaezzahra],
An ant colony based model to optimize parameters in industrial vision,
ELCVIA(16), No. 1, 2017, pp. 33-53.
WWW Link. 1708
BibRef

Liu, R.[Ruochen], Wang, R.[Ruinan], Yu, X.[Xin], An, L.[Lijia],
Shape automatic clustering-based multi-objective optimization with decomposition,
MVA(28), No. 5-6, August 2017, pp. 497-508.
WWW Link. 1708
BibRef

Chen, Y.Y.[Yong-Yong], Wang, Y.L.[Yong-Li], Li, M.Q.[Ming-Qiang], He, G.P.[Guo-Ping],
Augmented Lagrangian alternating direction method for low-rank minimization via non-convex approximation,
SIViP(11), No. 7, October 2017, pp. 1271-1278.
WWW Link. 1708
BibRef


Anirudh, R., Kailkhura, B., Thiagarajan, J.J., Bremer, P.T.,
Poisson Disk Sampling on the Grassmannnian: Applications in Subspace Optimization,
Diff-CVML17(690-698)
IEEE DOI 1709
Approximation algorithms, Manifolds, Measurement, Optimization, Principal component analysis, Silicon BibRef

Rosa, G.H.[Gustavo H.], Afonso, L.C.S.[Luis C. S.], Baldassin, A.[Alexandro], Papa, J.P.[João P.], Yang, X.S.[Xin-She],
Quaternionic Flower Pollination Algorithm,
CAIP17(II: 47-58).
Springer DOI 1708
BibRef

Zhang, Y.[Ying], Wang, H.W.[Hong-Wei], Wang, Y.B.[Yu-Bing], Guo, P.C.[Peng-Cheng],
A novel optimization algorithm for BP neural network based on RS-MEA,
ICIVC17(1073-1078)
IEEE DOI 1708
Convergence, Evolutionary computation, Indexes, Rough sets, BP neural network, attribute reduction, global optimal, mind evolutionary algorithm, rough, set BibRef

Zhu, M.K.[Ming-Kang], Chen, J.L.[Jian-Li],
Computational comparison of GRASP and DCTSP methods for the Traveling Salesman Problem,
ICIVC17(1044-1048)
IEEE DOI 1708
Annealing, GRASP, dynamic convexized method, traveling, salesman, problem BibRef

Dalmau-Cedeño, O.[Oscar], Oviedo, H.[Harry],
A Projection Method for Optimization Problems on the Stiefel Manifold,
MCPR17(84-93).
Springer DOI 1706
BibRef

Osmanlioglu, Y.[Yusuf], Ontañón, S.[Santiago], Hershberg, U.[Uri], Shokoufandeh, A.[Ali],
Efficient approximation of labeling problems with applications to immune repertoire analysis,
ICPR16(2410-2415)
IEEE DOI 1705
Approximation algorithms, Cost function, Distortion, Labeling, Linear programming, Measurement BibRef

Weissenberg, J., Riemenschneider, H., Dragon, R., Van Gool, L.J.,
Dilemma First Search for effortless optimization of NP-hard problems,
ICPR16(4154-4159)
IEEE DOI 1705
Algorithm design and analysis, Decision trees, Genetic algorithms, Inference algorithms, Optimization, Search problems, Vegetation BibRef

Luo, Z.J.[Zhi-Jian], Liao, D.P.[Dan-Ping], Qian, Y.T.[Yun-Tao],
Bound analysis of natural gradient descent in stochastic optimization setting,
ICPR16(4166-4171)
IEEE DOI 1705
Computer science, Convergence, Extraterrestrial measurements, Mirrors, Neural networks, Optimization, Bound Analysis, Mirror Gradient, Natural Gradient, Riemannian Space, Stochastic, Optimization BibRef

Awate, S.P., Dhar, M., Kulkarni, N.,
Robust kernel principal nested spheres,
ICPR16(402-407)
IEEE DOI 1705
Algorithm design and analysis, Data models, Kernel, Manifolds, Optimization, Principal component analysis, Robustness BibRef

Samejima, M.[Masaki], Matsushita, Y.[Yasuyuki],
Fast General Norm Approximation via Iteratively Reweighted Least Squares,
eHeritage16(II: 207-221).
Springer DOI 1704
BibRef

Shcherbatyi, I.[Iaroslav], Andres, B.[Bjoern],
Convexification of Learning from Constraints,
GCPR16(79-90).
Springer DOI 1611
BibRef

Matsuzawa, T.[Tomoki], Relator, R.[Raissa], Sese, J.[Jun], Kato, T.[Tsuyoshi],
Stochastic Dykstra Algorithms for Metric Learning with Positive Definite Covariance Descriptors,
ECCV16(VI: 786-799).
Springer DOI 1611
BibRef

Hafner, D.[David], Ochs, P.[Peter], Weickert, J.[Joachim], Reißel, M.[Martin], Grewenig, S.[Sven],
FSI Schemes: Fast Semi-Iterative Solvers for PDEs and Optimisation Methods,
GCPR16(91-102).
Springer DOI 1611
BibRef

Nakano, G.[Gaku],
A Versatile Approach for Solving PnP, PnPf, and PnPfr Problems,
ECCV16(III: 338-352).
Springer DOI 1611
BibRef

Beier, T.[Thorsten], Andres, B.[Björn], Köthe, U.[Ullrich], Hamprecht, F.A.[Fred A.],
An Efficient Fusion Move Algorithm for the Minimum Cost Lifted Multicut Problem,
ECCV16(II: 715-730).
Springer DOI 1611
BibRef

Kovnatsky, A.[Artiom], Glashoff, K.[Klaus], Bronstein, M.M.[Michael M.],
MADMM: A Generic Algorithm for Non-smooth Optimization on Manifolds,
ECCV16(V: 680-696).
Springer DOI 1611
BibRef

Talbot, H.[Hugues],
Discrete Calculus, Optimisation and Inverse Problems in Imaging,
DGCI16(18-27).
WWW Link. 1606
BibRef

Diamond, S., Boyd, S.,
Convex Optimization with Abstract Linear Operators,
ICCV15(675-683)
IEEE DOI 1602
Convex functions BibRef

Henry, M.[Morgane], Maitre, E.[Emmanuel], Perrier, V.[Valerie],
Optimal transport using Helmholtz-Hodge decomposition and first-order primal-dual algorithms,
ICIP15(4748-4752)
IEEE DOI 1512
Convex optimization BibRef

Zielosko, B.[Beata],
Global Optimization of Exact Association Rules Relative to Coverage,
PReMI15(428-437).
Springer DOI 1511
BibRef

Cheng, Y., Lopez, J.A., Camps, O., Sznaier, M.,
A convex optimization approach to robust fundamental matrix estimation,
CVPR15(2170-2178)
IEEE DOI 1510
BibRef

Dong, G.Z.[Guo-Zhi], Patrone, A.R.[Aniello Raffaele], Scherzer, O.[Otmar], Öktem, O.[Ozan],
Infinite Dimensional Optimization Models and PDEs for Dejittering,
SSVM15(678-689).
Springer DOI 1506
BibRef

Serra, J.[Jean], Kiran, B.R.[Bangalore Ravi],
Digitization of Partitions and Tessellations,
DGCI16(323-334).
WWW Link. 1606
BibRef
And:
Constrained Optimization on Hierarchies and Braids of Partitions,
ISMM15(229-240).
Springer DOI 1506
BibRef

Pavlovskaia, M.[Maira], Tu, K.W.[Ke-Wei], Zhu, S.C.[Song-Chun],
Mapping the Energy Landscape of Non-convex Optimization Problems,
EMMCVPR15(421-435).
Springer DOI 1504
BibRef

Liu, K.[Kangwei], Zhang, J.[Junge], Huang, K.Q.[Kai-Qi],
Improved Optimization Based on Graph Cuts for Discrete Energy Minimization,
ICPR14(2424-2429)
IEEE DOI 1412
Algorithm design and analysis BibRef

Eriksson, A.P.[Anders P.], Isaksson, M.[Mats],
Pseudoconvex Proximal Splitting for L-infinity Problems in Multiview Geometry,
CVPR14(4066-4073)
IEEE DOI 1409
Optimization. BibRef

Yuan, X.T.[Xiao-Tong], Liu, Q.S.[Qing-Shan],
Newton Greedy Pursuit: A Quadratic Approximation Method for Sparsity-Constrained Optimization,
CVPR14(4122-4129)
IEEE DOI 1409
Greedy Pursuit; Newton Method; Optimization; Sparsity Model BibRef

Tang, M.[Meng], Ben Ayed, I.[Ismail], Boykov, Y.[Yuri],
Pseudo-bound Optimization for Binary Energies,
ECCV14(V: 691-707).
Springer DOI 1408
BibRef

Xu, J.[Jia], Ithapu, V.K.[Vamsi K.], Mukherjee, L.[Lopamudra], Rehg, J.M.[James M.], Singh, V.[Vikas],
GOSUS: Grassmannian Online Subspace Updates with Structured-Sparsity,
ICCV13(3376-3383)
IEEE DOI 1403
Manifold optimization BibRef

Yang, S.[Shulin], Wang, J.[Jue], Shapiro, L.G.[Linda G.],
Supervised Semantic Gradient Extraction Using Linear-Time Optimization,
CVPR13(2826-2833)
IEEE DOI 1309
BibRef

Windheuser, T.[Thomas], Ishikawa, H.[Hiroshi], Cremers, D.[Daniel],
Generalized Roof Duality for Multi-Label Optimization: Optimal Lower Bounds and Persistency,
ECCV12(VI: 400-413).
Springer DOI 1210
BibRef

Mu, Y.D.[Ya-Dong], Wright, J.[John], Chang, S.F.[Shih-Fu],
Accelerated Large Scale Optimization by Concomitant Hashing,
ECCV12(I: 414-427).
Springer DOI 1210
BibRef

Kuang, Y.B.[Yu-Bin], Åström, K.[Kalle],
Numerically Stable Optimization of Polynomial Solvers for Minimal Problems,
ECCV12(III: 100-113).
Springer DOI 1210
BibRef

Brédif, M., Tournaire, O.,
Librjmcmc: An Open-source Generic C++ Library For Stochastic Optimization,
ISPRS12(XXXIX-B3:259-264).
DOI Link 1209
Code, Optimization. BibRef

Naroditsky, O.[Oleg], Daniilidis, K.[Kostas],
Optimizing polynomial solvers for minimal geometry problems,
ICCV11(975-982).
IEEE DOI 1201
BibRef

Akhtar, S.[Sohail], Abdel-Rahman, E.M.[Eihab M.], Ahmad, A.R.[Abdul-Rahim],
A New Fitness Based Adaptive Parameter Particle Swarm Optimizer,
CRV14(336-343)
IEEE DOI 1406
Acceleration BibRef

Akhtar, S.[Sohail], Ahmad, A.R.[Abdul-Rahim], Abdel-Rahman, E.M.[Eihab M.], Naqvi, T.,
A PSO Accelerated Immune Particle Filter for Dynamic State Estimation,
CRV11(72-79).
IEEE DOI 1105
PSO: Particle Swarm Optimization. Avoid local minima. BibRef

Chen, Y.S.[Yi-Song], Sun, J.W.[Jie-Wei], Wang, G.P.[Guo-Ping],
Minimizing Geometric Distance by Iterative Linear Optimization,
ICPR10(1-4).
IEEE DOI 1008
BibRef

Kohli, P.[Pushmeet], Lempitsky, V.[Victor], Rother, C.[Carsten],
Uncertainty Driven Multi-scale Optimization,
DAGM10(242-251).
Springer DOI 1009
multi-scale energy minimization BibRef

Olsson, C.[Carl], Kahl, F.[Fredrik], Hartley, R.I.[Richard I.],
Projective least-squares: Global solutions with local optimization,
CVPR09(1216-1223).
IEEE DOI 0906
BibRef

Olsson, C.[Carl], Byröd, M.[Martin], Kahl, F.[Fredrik],
Globally Optimal Least Squares Solutions for Quasiconvex 1D Vision Problems,
SCIA09(686-695).
Springer DOI 0906
BibRef

Kopylov, A.[Andrey],
Tree-serial dynamic programming for image processing,
ICPR08(1-4).
IEEE DOI 0812
Optimization technique. BibRef

Yang, F.Q.[Feng-Qin], Zhang, C.H.[Chang-Hai], Sun, T.[Tieli],
Comparison of Particle Swarm Optimization and Genetic Algorithm for HMM training,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Unger, M.[Markus], Pock, T.[Thomas], Bischof, H.[Horst],
Global Relabeling for Continuous Optimization in Binary Image Segmentation,
EMMCVPR11(104-117).
Springer DOI 1107
See also TVSeg: Interactive Total Variation Based Image Segmentation. BibRef

Huang, X.F.[Xiao-Fei],
Cooperative Optimization for Energy Minimization in Computer Vision: A Case Study of Stereo Matching,
DAGM04(302-309).
Springer DOI 0505
BibRef

Chapter on Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants continues in
Regression .


Last update:Sep 18, 2017 at 11:34:11