C. Kervrann, F. Heitz. A Hierarchical Markov Modeling Approach for the Segmentation and Tracking of Deformable Shapes. Graphical Models and Image Processing, 60(3):173-195, May 1998.
Download paper:
Adobe portable document (pdf)
Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.
In many applications of dynamic scene analysis, the objects or structures to be analyzed undergo deformations that have to be modeled. In this paper, we develop a hierarchical statistical modeling framework for the representation, segmentation, and tracking of 2D deformable structures in image sequences. The model relies on the specification of a template, on which global as well as local deformations are defined. Global deformations are modeled using a statistical modal analysis of the deformations observed on a representative population. Local deformations are represented by a (first-oder) Markov random process. A model-based segmentation of the scene is obtained by a joint bayesian estimation of global deformation parameters and local deformation variables. Spatial or spatio-temporal observations are considered in this estimation procedure, yielding an edge-based or a motion-based segmentation of the scene. The segmentation procedure is combined with a temporal tracking of the deformable structure over long image sequences, using a kalman filtering approach. This combined segmentation-tracking procedure has produced reliable extraction of deformable parts from long image sequences in adverse situations such as low signal-to-noise ratio, nongaussian noise, partial occlusions, or random initialization. The approach is demonstrated on a variety of synthetic as well as real-world image sequences featuring different classes of deformable objects
@article{Kervrann98b,
Author = {Kervrann, C. and Heitz, F.},
Title = {A Hierarchical Markov Modeling Approach for the Segmentation and Tracking of Deformable Shapes},
Journal = {Graphical Models and Image Processing},
Volume = {60},
Number = {3},
Pages = {173--195},
Month = {May},
Year = {1998}
}
Get EndNote Reference (.ref)
This document was translated automatically from BibTEX by bib2html (Copyright 2003 © Eric Marchand, INRIA, Vista Project).
