NDLI: Motion and Appearance Nonparametric Joint Entropy for Video Segmentation

Content Provider	Springer Nature Link
Author	Boltz, Sylvain Herbulot, Ariane Debreuve, Eric Barlaud, Michel Aubert, Gilles
Copyright Year	2008
Abstract	This paper deals with video segmentation based on motion and spatial information. Classically, the motion term is based on a motion compensation error (MCE) between two consecutive frames. Defining a motion-based energy as the integral of a function of the MCE over the object domain implicitly results in making an assumption on the MCE distribution: Gaussian for the square function and, more generally, parametric distributions for functions used in robust estimation. However, these assumptions are not necessarily appropriate. Instead, we propose to define the energy as a function of (an estimation of) the MCE distribution. This function was chosen to be a continuous version of the Ahmad-Lin entropy approximation, the purpose being to be more robust to outliers inherently present in the MCE. Since a motion-only constraint can fail with homogeneous objects, the motion-based energy is enriched with spatial information using a joint entropy formulation. The resulting energy is minimized iteratively using active contours. This approach provides a general framework which consists in defining a statistical energy as a function of a multivariate distribution, independently of the features associated with the object of interest. The link between the energy and the features observed or computed on the video sequence is then made through a nonparametric, kernel-based distribution estimation. It allows for example to keep the same energy definition while using different features or different assumptions on the features.
Starting Page	242
Ending Page	259
Page Count	18
File Format	PDF
ISSN	09205691
Journal	International Journal of Computer Vision
Volume Number	80
Issue Number	2
e-ISSN	15731405
Language	English
Publisher	Springer US
Publisher Date	2008-01-19
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Spatio-temporal segmentation Nonparametric distribution Joint entropy Active contour Pattern Recognition Image Processing and Computer Vision Artificial Intelligence (incl. Robotics) Computer Imaging, Vision, Pattern Recognition and Graphics
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Computer Vision and Pattern Recognition Software

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