Detecting parametric objects in large scenes by Monte Carlo sampling - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Article Dans Une Revue International Journal of Computer Vision Année : 2014

Detecting parametric objects in large scenes by Monte Carlo sampling

Yannick Verdie
  • Fonction : Auteur
  • PersonId : 904861
Florent Lafarge
  • Fonction : Auteur
  • PersonId : 833647

Résumé

Point processes constitute a natural extension of Markov Random Fields (MRF), designed to handle parametric objects. They have shown efficiency and competitiveness for tackling object extraction problems in vision. Simulating these stochastic models is however a difficult task. The performances of the existing samplers are limited in terms of computation time and convergence stability, especially on large scenes. We propose a new sampling procedure based on a Monte Carlo formalism. Our algorithm exploits the Markovian property of point processes to perform the sampling in parallel. This procedure is embedded into a data-driven mechanism so that the points are distributed in the scene in function of spatial information extracted from the input data. The performances of the sampler are analyzed through a set of experiments on various object detection problems from large scenes, including comparisons to the existing algorithms. The sampler is also tested as optimization algorithm for MRF-based labeling problems.
Fichier principal
Vignette du fichier
IJCV.pdf (14.29 Mo) Télécharger le fichier
Vignette du fichier
hal-00843022.png (844.55 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Format : Figure, Image
Loading...

Dates et versions

hal-00843022 , version 1 (10-07-2013)

Identifiants

Citer

Yannick Verdie, Florent Lafarge. Detecting parametric objects in large scenes by Monte Carlo sampling. International Journal of Computer Vision, 2014, 106 (1), pp.57-75. ⟨10.1007/s11263-013-0641-0⟩. ⟨hal-00843022⟩
295 Consultations
3182 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More