Titlebook: Energy Minimization Methods in Computer Vision and Pattern Recognition; Third International Mário Figueiredo,Josiane Zerubia,Anil K. Jain

Panacea

Metric Similarities Learning through Examples: An Application to Shape Retrievalariant to rotation and scaling). Moreover, we show that much more flexibility can be added by non-rigid deformation of the induced feature space. Defining an adequate Bayesian users model, we describe an estimation procedure based on the maximisation of the underlying log-likehood function.

制造

Designing the Minimal Structure of Hidden Markov Model by Bisimulationion allows to merge HMM states in order to obtain a minimal set that do not significantly affect model performances. The approach has been tested on DNA sequence modeling and 2D shape classification. Results are presented in function of reduction rates, classification performances, and noise sensitivity.

Intervention

amenity

Articulated Object Tracking via a Genetic Algorithmrence system, they are the same from different cameras, so more cameras are easily added, increasing the constraints over the same number of variables. Several successful experiments are presented for an arm motion and a leg motion from two and three cameras.

mortuary

Learning Matrix Space Image Representationse basis vectors and the projection coefficients. Since our fundamental goal is classification and indexing, we develop a matrix space distance measure between images in the training set. Results are shown on face images and natural scenes.

乞丐

Path Based Pairwise Data Clustering with Application to Texture Segmentationiterion considers two objects as similar if there exists a mediating intra cluster path without an edge with large cost. The cost function is optimized in a multi-scale fashion. This new path based clustering concept is applied to segment textured images with strong texture gradients based on dissimilarities between image patches.

agonist

Energy Minimization Methods in Computer Vision and Pattern RecognitionThird International

Mitigate

正常

A Double-Loop Algorithm to Minimize the Bethe Free Energywork to the more general Kikuchi approximation [.] which includes the Bethe free energy as a special case. It is anticipated that these double-loop algorithms will be useful for solving optimization problems in computer vision and other applications.

A精确的

A Hierarchical Markov Random Field Model for Figure-Ground Segregatione provides an in-teresting platform for us to investigate the interaction of local decision rules and global representations, as well as to reason about the rationales underlying some of recent psychological and neurophysiological findings related to figure-ground segregation.