PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Depth map calculation for a variable number of moving objects using Markov sequential object processes
M.N.M. van Lieshout
(2007) EURANDOM, Eindhoven.

Abstract

We advocate the use of Markov sequential object processes for tracking a variable number of moving objects through a video frame with a view towards depth map calculation. A regression model based on a sequential object process is related to the Hough transform; regularization terms are incorporated to control within and between frame object interactions. We construct a Markov chain Monte Carlo method for finding the optimal tracks and associated depth maps and illustrate the approach on a synthetic data set and a sport sequence.

EPrint Type:Other
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:3067
Deposited By:Marie-Colette van Lieshout
Deposited On:29 November 2007