13.3.8.3 Energy Minimization, Energy Maximization Computation, Function Solving, Optimizations

Greig, D., Porteous, B., Seheult, A.,
Exact Maximum a Posterori Estimation for Binary Images,
RoyalStat(B: 51), No. 2, 1989, pp. 271-279. Show min-cut/max-flow algorithms can be used to minimize energy functions in vision. BibRef 8900

Salerno, E.[Emanuele],
Guest Editorial: Fast Energy-Minimization-Based Imaging and Vision Techniques,
RealTimeImg(7), No. 1, February 2001, pp. 1-2.
WWW Version. 0106
Special issue introduction. BibRef

Pérez, P.[Patrick], Chardin, A.[Annabelle], Laferté, J.M.[Jean-Marc],
Noniterative manipulation of discrete energy-based models for image analysis,
PR(33), No. 4, April 2000, pp. 573-586.
WWW Version. 0002
BibRef

Figueiredo, M.A.T.[Mario A.T.], Hancock, E.R.[Edwin R.], Pelillo, M.[Marcello], Zerubia, J.B.[Josiane B.],
Guest editors' Introduction to the special section on energy minimization methods in computer vision and pattern recognition,
PAMI(25), No. 11, November 2003, pp. 1361-1363.
IEEE Abstract. BibRef 0311
And: PAMI(26), No. 2, February 2004, pp. 145-146.
IEEE Abstract. 0311
Pose the task as the minimization of an energy measure, then a variety of optimization methods can be applied. Includes relaxation, regularization, active contours, Markov models. BibRef

Kolmogorov, V.,
Convergent Tree-Reweighted Message Passing for Energy Minimization,
PAMI(28), No. 10, October 2006, pp. 1568-1583.
IEEE DOI Link 0609
See also MAP Estimation via Agreement on (Hyper)Trees: Message-Passing and Linear-Programming Approaches. BibRef

Paragios, N.[Nikos], Zabih, R.[Ramin],
Discrete optimization in computer vision,
CVIU(112), No. 1, October 2008, pp. 1-2.
WWW Version. 0810
BibRef
And: Corrigendum: CVIU(113), No. 4, April 2009, pp. 588.
Elsevier DOI Link
WWW Version. 0903
Special section introduction. BibRef

Komodakis, N.[Nikos], Tziritas, G.[Georgios], Paragios, N.[Nikos],
Performance vs computational efficiency for optimizing single and dynamic MRFs: Setting the state of the art with primal-dual strategies,
CVIU(112), No. 1, October 2008, pp. 14-29.
WWW Version. 0810
BibRef
Earlier:
Fast, Approximately Optimal Solutions for Single and Dynamic MRFs,
CVPR07(1-8).
IEEE DOI Link
PDF Version. 0706
Code, Alignment.
WWW Version. BibRef
Earlier: A1, A3, A2:
MRF Optimization via Dual Decomposition: Message-Passing Revisited,
ICCV07(1-8).
IEEE DOI Link 0710
Nonlinear programming techniques. Markov random fields; Linear programming; Primal-dual schema; Discrete optimization; Graph cuts BibRef

Komodakis, N.[Nikos], Paragios, N.[Nikos],
Beyond pairwise energies: Efficient optimization for higher-order MRFs,
CVPR09(2985-2992).
IEEE DOI Link 0906
BibRef
Earlier:
Beyond Loose LP-Relaxations: Optimizing MRFs by Repairing Cycles,
ECCV08(III: 806-820).
Springer DOI Link 0810
BibRef

Preusser, T.[Tobias], Scharr, H.[Hanno], Krajsek, K.[Kai], Kirby, R.M.[Robert M.],
Building Blocks for Computer Vision with Stochastic Partial Differential Equations,
IJCV(80), No. 3, December 2008, pp. xx-yy.
Springer DOI Link 0810
Get PDF in addition to the solution to the value at the pixel. BibRef

Rao, S.[Sudhir], de Medeiros Martins, A.[Allan], Principe, J.C.[Jose C.],
Mean shift: An information theoretic perspective,
PRL(30), No. 3, 1 February 2009, pp. 222-230.
Elsevier DOI Link
WWW Version. 0804
Mean shift; Information theoretic learning; Renyi's entropy Analysis of mean shift. Gaussian bluring MS and Gaussian MS. BibRef

Simila, T.[Timo], Tikka, J.[Jarkko],
Combined input variable selection and model complexity control for nonlinear regression,
PRL(30), No. 3, 1 February 2009, pp. 231-236.
Elsevier DOI Link
WWW Version. 0804
Regression; Function approximation; MLP; Multilayer perceptron; Input variable selection; Hidden node selection BibRef

Rodriguez, P.[Paul], Wohlberg, B.[Brendt],
Efficient Minimization Method for a Generalized Total Variation Functional,
IP(18), No. 2, February 2009, pp. 322-332.
IEEE DOI Link 0901
BibRef
And:
A generalized vector-valued total variation algorithm,
ICIP09(1309-1312).
IEEE DOI Link 0911
BibRef

Bar, L.[Leah], Sapiro, G.[Guillermo],
Generalized Newton-Type Methods For Energy Formulations In Image Processing,
SIIMS(2), No. 2, 2009, pp. 508-531.
WWW Version.
WWW Version. BibRef 0900
Earlier:
Generalized Newton methods for energy formulations in image procesing,
ICIP08(809-812).
IEEE DOI Link 0810
Newton method; variational methods; trust-region; generalized inner product; geometric active contours; deblurring BibRef

Wang, X.Y.[Xing-Yuan], Song, W.[Wenjing], Zou, L.[Lixian],
Julia Set of the Newton Method for Solving Some Complex Exponential Equation,
IJIG(9), No. 2, April 2009, pp. 153-169. 0905
BibRef

Hwang, J.K., Li, Y.P.,
Variable Step-Size LMS Algorithm With a Gradient-Based Weighted Average,
SPLetters(16), No. 12, December 2009, pp. 1043-1046.
IEEE DOI Link 0909
BibRef

Yu, D.[Dong], Deng, L.[Li], Acero, A.[Alex],
Using continuous features in the maximum entropy model,
PRL(30), No. 14, 15 October 2009, pp. 1295-1300,.
Elsevier DOI Link
WWW Version. 0909
Maximum entropy principle; Spline interpolation; Continuous feature; Maximum entropy model; Moment constraint; Distribution constraint BibRef

Huda, S.[Shamsul], Yearwood, J.[John], Togneri, R.[Roberto],
A stochastic version of Expectation Maximization algorithm for better estimation of Hidden Markov Model,
PRL(30), No. 14, 15 October 2009, pp. 1301-1309,.
Elsevier DOI Link
WWW Version. 0909
Hidden Markov Model; Expectation Maximization; Speech recognition; Constraint-based Evolutionary Algorithm; Stochastic EM BibRef

Leung, S.Y.[Shing-Yu], Liang, G.[Gang], Solna, K.[Knut], Zhao, H.[Hongkai],
Expectation-Maximization Algorithm With Local Adaptivity,
SIIMS(2), No. 3, 2009, pp. 834-857.
WWW Version.
WWW Version. expectation-maximization algorithm; Gaussian mixture model; posterior probability; local adaptivity; image segmentation BibRef 0900

Xu, S.G.[Song-Gang], Zhang, Y.X.[Yun-Xiang], Yong, J.H.[Jun-Hai],
A Fast Sweeping Method for Computing Geodesics on Triangular Manifolds,
PAMI(32), No. 2, February 2010, pp. 231-241.
IEEE DOI Link 1001
Computations for graphics applications. BibRef

Zeng, T., Ng, M.K.[Michael K.],
On the Total Variation Dictionary Model,
IP(19), No. 3, March 2010, pp. 821-825.
IEEE DOI Link 1003
BibRef

Pang, Y., Li, X., Yuan, Y.,
Robust Tensor Analysis With L1-Norm,
CirSysVideo(20), No. 2, February 2010, pp. 172-178.
IEEE DOI Link 1003
General computational technique. BibRef

Darbon, J.[Jerome], Ciril, I.[Igor], Marquina, A.[Antonio], Chan, T.F.[Tony F.], Osher, S.[Stanley],
A note on the Bregmanized Total Variation and dual forms,
ICIP09(2965-2968).
IEEE DOI Link 0911
BibRef

Fadili, J.M.[Jalal M.], Peyre, G.[Gabriel],
Total variation projection with first order schemes,
ICIP09(1325-1328).
IEEE DOI Link 0911
BibRef

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

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

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

Koutis, I.[Ioannis], Miller, G.L.[Gary L.], Tolliver, D.A.[David A.],
Combinatorial Preconditioners and Multilevel Solvers for Problems in Computer Vision and Image Processing,
ISVC09(I: 1067-1078).
Springer DOI Link 0911
BibRef

Liao, F.[Fei],
High Accurate theta-Scheme for Solving BSDEs,
CISP09(1-5).
IEEE DOI Link 0910
BibRef

Yang, G.[Gelan], Xu, X.[Xue], Jin, H.X.[Hui-Xia],
Semi-Supervised Regression via Local Block Coordinate,
CISP09(1-4).
IEEE DOI Link 0910
BibRef

An, Z.J.[Zhi-Juan], Zhang, M.[Min], Su, H.T.[Hong-Tao],
Novel Fast Subspace Decomposition Using Lanczos Recursion,
CISP09(1-4).
IEEE DOI Link 0910
BibRef

Xing, G.X.[Gao-Xiang], Cai, Z.M.[Zhi-Ming],
A Sidelobe-Constraint Direct Data Domain Least Square Algorithm,
CISP09(1-4).
IEEE DOI Link 0910
BibRef

Wang, W.X.[Wei-Xiang], Shang, Y.L.[You-Lin],
A Novel Transforming Function for Nonlinear Equations,
CISP09(1-4).
IEEE DOI Link 0910
BibRef

Duan, C.Y.[Cong-Ying],
A New Analysis on PVL Model Reduction Using Solutions of Linear Systems by the Lanczos Method,
CISP09(1-5).
IEEE DOI Link 0910
BibRef

Liu, X.H.[Xiao-Hua], Deng, H.X.[Hong-Xia],
A Modified Method of State-Estimator Designing for Non-Uniformly Sampled System,
CISP09(1-5).
IEEE DOI Link 0910
BibRef

Schlesinger, D.[Dmitrij],
General Search Algorithms for Energy Minimization Problems,
EMMCVPR09(84-97).
Springer DOI Link 0908
BibRef

Yildiz, A.[Alparslan], Akgul, Y.S.[Yusuf Sinan],
A Gradient Descent Approximation for Graph Cuts,
DAGM09(312-321).
Springer DOI Link 0909
BibRef

Xu, L.L.[Lin-Li], Li, W.[Wenye], Schuurmans, D.[Dale],
Fast normalized cut with linear constraints,
CVPR09(2866-2873).
IEEE DOI Link 0906
Optimal normalized cut has proven to be NP-hard. Linear constraints to incorporate prior information. BibRef

Nowozin, S.[Sebastian], Lampert, C.H.[Christoph H.],
Global connectivity potentials for random field models,
CVPR09(818-825).
IEEE DOI Link 0906
BibRef

Reddy, D.[Dikpal], Agrawal, A.[Amit], Chellappa, R.[Rama],
Enforcing integrability by error correction using L1-minimization,
CVPR09(2350-2357).
IEEE DOI Link 0906
BibRef

Li, H.D.[Hong-Dong],
Efficient reduction of L-infinity geometry problems,
CVPR09(2695-2702).
IEEE DOI Link 0906
BibRef

Zach, C.[Christopher], Niethammer, M.[Marc], Frahm, J.M.[Jan-Michael],
Continuous maximal flows and Wulff shapes: Application to MRFs,
CVPR09(1911-1918).
IEEE DOI Link 0906
Extend the continuous, isotropic maximal flow framework to the anisotropic case. BibRef

Kim, W.S.[Won-Sik], Lee, K.M.[Kyoung Mu],
Markov Chain Monte Carlo combined with deterministic methods for Markov random field optimization,
CVPR09(1406-1413).
IEEE DOI Link 0906
Analysis of the issues and techniques for computation methods in energy minimization. BibRef

Okatani, T.[Takayuki], Deguchi, K.[Koichiro],
On bias correction for geometric parameter estimation in computer vision,
CVPR09(959-966).
IEEE DOI Link 0906
Bias in maximum likelihood estimation techniques due to geometric configurations. BibRef

Gould, S.[Stephen], Amat, F.[Fernando], Koller, D.[Daphne],
Alphabet SOUP: A framework for approximate energy minimization,
CVPR09(903-910).
IEEE DOI Link 0906
BibRef

Rother, C.[Carsten], Kohli, P.[Pushmeet], Feng, W.[Wei], Jia, J.Y.[Jia-Ya],
Minimizing sparse higher order energy functions of discrete variables,
CVPR09(1382-1389).
IEEE DOI Link 0906
BibRef

Cetingul, H.E.[Hasan Ertan], Vidal, R.[Rene],
Intrinsic mean shift for clustering on Stiefel and Grassmann manifolds,
CVPR09(1896-1902).
IEEE DOI Link 0906
An alternative formulation. 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 Link 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 Link 0906
BibRef

Wang, J.F.[Jun-Feng], Luo, J.W.[Jun-Wei],
Performance analysis of an improved variable tap-length LMS algorithm,
IASP09(377-380).
IEEE DOI Link 0904
least mean square BibRef

Zhang, J.[Jie], Liu, Z.H.[Zhen-Hua], Wen, Q.Y.[Qiao-Yan],
Constructions of resilient functions over finite fields,
IASP09(317-319).
IEEE DOI Link 0904
BibRef

Li, Y.Y.[Yan-Yan], Wang, W.H.[Wei-Hong], Gu, G.M.[Guo-Min],
The simulation of parametric fountain based on Direct3D,
IASP09(237-240).
IEEE DOI Link 0904
BibRef

Yao, Q.[Qiguo], Liu, G.P.[Guo-Ping],
Simulation and analysis of Lorenz system's dynamics characteristics,
IASP09(427-429).
IEEE DOI Link 0904
BibRef

Su, Q.F.[Qi-Fang],
Perturbation analysis for linear systems,
IASP09(430-433).
IEEE DOI Link 0904
BibRef

Bicego, M., Gonzalez-Jimenez, D., Grosso, E., Alba Castro, J.L.,
Generalized Gaussian distributions for sequential data classification,
ICPR08(1-4).
IEEE DOI Link 0812
Vs. HMM modeling techniques. BibRef

Felsberg, M.[Michael],
On second order operators and quadratic operators,
ICPR08(1-4).
IEEE DOI Link 0812
BibRef

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

Ren, H.J.[Hai-Jun], Wu, L.[Liang], Neskovic, P.[Predrag], Cooper, L.[Leon],
Approximating a non-homogeneous HMM with Dynamic Spatial Dirichlet Process,
ICPR08(1-4).
IEEE DOI Link 0812
BibRef

Yang, F.[Fengqin], Zhang, C.[Changhai], Sun, T.[Tieli],
Comparison of Particle Swarm Optimization and Genetic Algorithm for HMM training,
ICPR08(1-4).
IEEE DOI Link 0812
BibRef

Ko, A.H.R.[Albert Hung-Ren], Sabourin, R.[Robert], de Souza Britto, A.[Alceu],
A new HMM training and testing scheme,
ICPR08(1-4).
IEEE DOI Link 0812
BibRef

Missaoui, O.[Oualid], Frigui, H.[Hichem],
Optimal feature weighting for the discrete HMM,
ICPR08(1-4).
IEEE DOI Link 0812
BibRef
And:
Optimal feature weighting for the continuous HMM,
ICPR08(1-4).
IEEE DOI Link 0812
BibRef

Datta, R.[Ritendra], Hu, J.Y.[Jian-Ying], Ray, B.[Bonnie],
On efficient Viterbi decoding for hidden semi-Markov models,
ICPR08(1-4).
IEEE DOI Link 0812
BibRef

Heo, G.Y.[Gyeong-Yong], Gader, P.[Paul],
Prior-updating ensemble learning for discrete HMM,
ICPR08(1-4).
IEEE DOI Link 0812
BibRef

Rakotondralambo, J., Michaille, G., Brouzet, R., Puech, W.,
Variational approximation of a constraint signal by a Mumford-Shah type energy functional,
IPTA08(1-5).
IEEE DOI Link 0811
BibRef

Müller, T.[Thomas], Lenz, C.[Claus], Barner, S.[Simon], Knoll, A.[Alois],
Accelerating Integral Histograms Using an Adaptive Approach,
ICISP08(209-217).
Springer DOI Link 0807
BibRef

Reznik, Y.A.[Yuriy A.], Hinds, A.T.[Arianne T.], Mitchell, J.L.[Joan L.],
Improved precision of fixed-point algorithms by means of common factors,
ICIP08(2344-2347).
IEEE DOI Link 0810
BibRef

Ranganathan, A.[Ananth], Yang, M.H.[Ming-Hsuan],
Online Sparse Matrix Gaussian Process Regression and Vision Applications,
ECCV08(I: 468-482).
Springer DOI Link 0810
BibRef

Szummer, M.[Martin], Kohli, P.[Pushmeet], Hoiem, D.[Derek],
Learning CRFs Using Graph Cuts,
ECCV08(II: 582-595).
Springer DOI Link 0810
BibRef

Grady, L.[Leo],
A Lattice-Preserving Multigrid Method for Solving the Inhomogeneous Poisson Equations Used in Image Analysis,
ECCV08(II: 252-264).
Springer DOI Link 0810
BibRef

Jung, H.Y.[Ho Yub], Lee, K.M.[Kyoung Mu], Lee, S.U.[Sang Uk],
Toward Global Minimum through Combined Local Minima,
ECCV08(IV: 298-311).
Springer DOI Link 0810
BibRef

Kukelova, Z.[Zuzana], Bujnak, M.[Martin], Pajdla, T.[Tomas],
Automatic Generator of Minimal Problem Solvers,
ECCV08(III: 302-315).
Springer DOI Link 0810
BibRef

Pock, T.[Thomas], Schoenemann, T.[Thomas], Graber, G.[Gottfried], Bischof, H.[Horst], Cremers, D.[Daniel],
A Convex Formulation of Continuous Multi-label Problems,
ECCV08(III: 792-805).
Springer DOI Link 0810
BibRef

Trobin, W.[Werner], Pock, T.[Thomas], Cremers, D.[Daniel], Bischof, H.[Horst],
Continuous Energy Minimization Via Repeated Binary Fusion,
ECCV08(IV: 677-690).
Springer DOI Link 0810
BibRef

Ali, A.M.[Asem M.], Farag, A.A.[Aly A.], Gimel'farb, G.L.[Georgy L.],
Optimizing Binary MRFs with Higher Order Cliques,
ECCV08(III: 98-111).
Springer DOI Link 0810
Analysis of MRFs to use pairwise results at higher orders. Energy minimization. BibRef

Schlesinger, D.[Dmitrij],
Exact Solution of Permuted Submodular MinSum Problems,
EMMCVPR07(28-38).
Springer DOI Link 0708
Energy Minimization Task. BibRef

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

Toh, K.A.[Kar-Ann],
Global Energy Minimization: A Transformation Approach,
EMMCVPR01(391-406).
Springer DOI Link 0205
BibRef

Trytten, D.A., and Tuceryan, M.,
Segmentation and Grouping of Object Boundaries Using Energy Minimization,
CVPR91(730-731).
IEEE Abstract. BibRef 9100

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