Bayesian selection of scaling laws for motion modeling in images

Proceedings of the IEEE International Conference on Computer Vision

Volumn , Issue , 2009, Pages 971-978

  Héas, Patrick ^a   Mémin, Etienne ^a   Heitz, Dominique ^b   Mininni, Pablo D ^c  

^a INRIA   (France)

^b CEMAGREF   (France)

^c UNIVERSIDAD DE BUENOS AIRES   (Argentina)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN; BAYESIAN EVIDENCE; BEST STATE; CONSTRAINED MINIMIZATION PROBLEM; DIFFERENT SCALE; DUAL PROBLEM; FIRST-ORDER; FLOW ESTIMATION; IMAGE DATA; IMAGE SEQUENCE; LAGRANGIAN DUALITY; MOTION ESTIMATOR; MOTION MODELING; MOTION MODELS; MULTISCALES; NON-PARAMETRIC; OPTIMAL REGULARIZATION; PHYSICAL QUANTITIES; REGULARIZER; SECOND LEVEL; SELF-SIMILAR; SELF-SIMILAR PROCESS; STATISTICAL STRUCTURES; SYNTHETIC IMAGES; TURBULENCE CHARACTERIZATION; TURBULENT MOTION;

BAYESIAN NETWORKS; COMPUTER VISION; LIGHT MEASUREMENT; MOTION ESTIMATION; OPTIMIZATION; TURBULENCE;

PARAMETER ESTIMATION;

EID: 77953200281     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2009.5459353     Document Type: Conference Paper

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