Depth map calculation for a variable number of moving objects using Markov sequential object processes

M.N.M. Lieshout, van

Research output: Contribution to journalArticleAcademicpeer-review

7 Citations (Scopus)

Abstract

We advocate the use of Markov sequential object processes for tracking a variable number of moving objects through video frames with a view towards depth calculation. A regression model based on a sequential object process quantifies goodness of fit; 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 depths and illustrate the approach on a synthetic data set as well as a sports sequence.
Original languageEnglish
Pages (from-to)1308-1312
JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
Volume30
Issue number7
DOIs
Publication statusPublished - 2008

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