Damen, D and Hogg, DC (2012) Detecting Carried Objects from Sequences of Walking Pedestrians. IEEE Transactions on Pattern Analysis and Machine Intelligence, 34 (6). 1056 - 1067 (12). ISSN 0162-8828
Abstract
This paper proposes a method for detecting objects carried by pedestrians, such as backpacks and suitcases, from video sequences. In common with earlier work [14], [16] on the same problem, the method produces a representation of motion and shape (known as a temporal template) that has some immunity to noise in foreground segmentations and phase of the walking cycle. Our key novelty is for carried objects to be revealed by comparing the temporal templates against view-specific exemplars generated offline for unencumbered pedestrians. A likelihood map of protrusions, obtained from this match, is combined in a Markov random field for spatial continuity, from which we obtain a segmentation of carried objects using the MAP solution. We also compare the previously used method of periodicity analysis to distinguish carried objects from other protrusions with using prior probabilities for carried-object locations relative to the silhouette. We have re-implemented the earlier state of the art method [14] and demonstrate a substantial improvement in performance for the new method on the PETS2006 dataset. The carried-object detector is also tested on another outdoor dataset. Although developed for a specific problem, the method could be applied to the detection of irregularities in appearance for other categories of object that move in a periodic fashion.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2012, IEEE. This is an author produced version of a paper published in IEEE Transactions on Pattern Analysis and Machine Intelligence. Uploaded in accordance with the publisher's self-archiving policy. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. |
Keywords: | Baggage detection; carried-object detection; silhouette analysis; temporal templates; template matching; periodicity analysis |
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) > Artificial Intelligence & Biological Systems (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 13 May 2013 14:26 |
Last Modified: | 23 Jun 2023 21:33 |
Published Version: | http://dx.doi.org/10.1109/TPAMI.2011.205 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers |
Identification Number: | 10.1109/TPAMI.2011.205 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:75543 |