Show simple item record

dc.contributor.authorKim, Du Yong
dc.contributor.authorJeon, M.
dc.identifier.citationKim, D.Y. and Jeon, M. 2015. Robust multi-Bernoulli filtering for visual tracking, pp. 47-52: Institute of Electrical and Electronics Engineers Inc.

To achieve reliable multi-object filtering in vision application, it is of great importance to determine appropriate model parameters. Parameters such as motion and measurement noise covariance can be chosen based on the image frame rate and the property of the designed detector. However, it is not trivial to obtain the average number of false positive measurements or detection probability due to the arbitrary visual scene characteristics from illumination condition or different fields of view. In this paper, we introduce the recently proposed robust multi-Bernoulli filter to deal with unknown clutter rate and detection profile in visual tracking applications. The robust multi-Bernoulli filter treats false positive responses as a special type of target so that the unknown clutter rate is estimated based on the estimated number of clutter targets. Performance evaluation with real videos demonstrates the effectiveness of the robust multi-Bernoulli filter and comparison results with the standard multi-object tracking algorithm show its reliability.

dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.titleRobust multi-Bernoulli filtering for visual tracking
dc.typeConference Paper
dcterms.source.title2014 International Conference on Control, Automation and Information Sciences, ICCAIS 2014
dcterms.source.series2014 International Conference on Control, Automation and Information Sciences, ICCAIS 2014
curtin.departmentDepartment of Electrical and Computer Engineering
curtin.accessStatusFulltext not available

Files in this item


There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record