Tavanai, A, Sridhar, M, Chinellato, E et al. (2 more authors) (2015) Joint Tracking and Event Analysis for Carried Object Detection. In: Xie, X, Jones, MW and Tam, GKL, (eds.) Proceedings of the 26th British Machine Vision Conference (BMVC 2015). 26th British Machine Vision Conference (BMVC 2015), 07-11 Sep 2015, Swansea, UK. BMVA Press , 79.1-79.11. ISBN 1-901725-53-7
Abstract
This paper proposes a novel method for jointly estimating the track of a moving object and the events in which it participates. The method is intended for dealing with generic objects that are hard to localise and track with the performance of current detection algorithms - our focus is on events involving carried objects. The tracks for other objects with which the target object interacts (e.g. the carrying person) are assumed to be given. The method is posed as maximisation of a posterior probability defined over event sequences and temporally-disjoint subsets of the tracklets from an earlier tracking process. The probability function is a Hidden Markov Model coupled with a term that penalises non-smooth tracks and large gaps in the observed data. We evaluate the method using tracklets output by three state of the art trackers on the new created MINDSEYE2015 dataset and demonstrate improved performance.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | (c) 2015. The copyright of this document resides with its authors. It may be distributed unchanged freely in print or electronic forms. |
Keywords: | Carried Object Detection; Tracking; Event Analysis; Event Recognition; Object Tracking |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Funding Information: | Funder Grant number EU - European Union 287752 DARPA W911NF |
Depositing User: | Symplectic Publications |
Date Deposited: | 28 Aug 2015 15:15 |
Last Modified: | 12 Dec 2024 11:18 |
Published Version: | https://bmva-archive.org.uk/bmvc/2015/papers/paper... |
Status: | Published |
Publisher: | BMVA Press |
Identification Number: | 10.5244/C.29.79 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:88532 |