Particle Filtering for Robust Single Camera Localisation

M Pupilli, A Calway

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


This paper summarises recent work on vision based localisation of a moving camera using particle filtering. We are interested in real-time operation for applications in mobile and wearable computing, in which the camera is worn or held by a user. Specifically, we aim for localisation algorithms which are robust to the real-life motions associated with human activity and to the dynamic clutter encountered in real environments. Particle filtering provides greater generality than previous approaches, enabling it to deal with the multi-modal uncertainties characteristic of such operating conditions. We present an overview of the methodology and experimental results for different tracking scenarios, with and without prior knowledge of scene structure.
Translated title of the contributionParticle Filtering for Robust Single Camera Localisation
Original languageEnglish
Title of host publicationUnknown
Publication statusPublished - May 2006

Bibliographical note

Conference Proceedings/Title of Journal: First International Workshop on Mobile Vision

Fingerprint Dive into the research topics of 'Particle Filtering for Robust Single Camera Localisation'. Together they form a unique fingerprint.

Cite this