Real-Time Camera Tracking Using a Particle Filter

M Pupilli, A Calway

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

104 Citations (Scopus)

Abstract

We describe a particle filtering method for vision based tracking of a hand held calibrated camera in real-time. The ability of the particle filter to deal with non-linearities and non-Gaussian statistics suggests the potential to provide improved robustness over existing approaches, such as those based on the Kalman filter. In our approach, the particle filter provides recursive approximations to the posterior density for the 3-D motion parameters. The measurements are inlier/outlier counts of likely correspondence matches for a set of salient points in the scene. The algorithm is simple to implement and we present results illustrating good tracking performance using a `live' camera. We also demonstrate the potential robustness of the method, including the ability to recover from loss of track and to deal with severe occlusion.
Translated title of the contributionReal-Time Camera Tracking Using a Particle Filter
Original languageEnglish
Title of host publicationUnknown
PublisherBMVA Press
Pages519 - 528
Number of pages9
Publication statusPublished - Sep 2005

Bibliographical note

Conference Proceedings/Title of Journal: Proceedings of the British Machine Vision Conference

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