File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Conference Paper: A Bag-of-Gait Model for Gait Recognition

TitleA Bag-of-Gait Model for Gait Recognition
Authors
Issue Date2012
PublisherCSREA Press.
Citation
Proceedings of The 2012 International Conference on Image Processing, Computer Vision, and Pattern Recognition (IPCV 2012), Las Vegas, NV, USA, 16-19 July 2012, v. 2, p. 871-876 How to Cite?
AbstractIn this paper, we propose a novel gait recognition method based on a bag-of-gait model. In the proposed method, the image sequence of a walking person is encoded by a codebook consisting of a list of code words denoting different walking stages; then, this image sequence is represented by a feature vector denoting the existence of the code words, which is further used for classification. Unlike most of previous gait recognition methods, there is no need to estimate gait period in the proposed method. Moreover, the proposed method is capable of recognizing the gait when the observed gait period is incomplete which caused by occlusion or short appearance time. The method is evaluated on a dataset consisting of 151 subjects with four different walking conditions using four-fold cross-validation. The result shows the effectiveness of the proposed method and the state-of-art result is achieved on that dataset.
DescriptionSession 4-IPCV: Biometrics: Gait, Fingerprint, Palmprint, and Knuckle Identification
Persistent Identifierhttp://hdl.handle.net/10722/223914
ISBN

 

DC FieldValueLanguage
dc.contributor.authorQin, J-
dc.contributor.authorLuo, T-
dc.contributor.authorShao, W-
dc.contributor.authorChung, RHY-
dc.contributor.authorChow, KP-
dc.date.accessioned2016-03-18T02:32:03Z-
dc.date.available2016-03-18T02:32:03Z-
dc.date.issued2012-
dc.identifier.citationProceedings of The 2012 International Conference on Image Processing, Computer Vision, and Pattern Recognition (IPCV 2012), Las Vegas, NV, USA, 16-19 July 2012, v. 2, p. 871-876-
dc.identifier.isbn978-160132225-8-
dc.identifier.urihttp://hdl.handle.net/10722/223914-
dc.descriptionSession 4-IPCV: Biometrics: Gait, Fingerprint, Palmprint, and Knuckle Identification-
dc.description.abstractIn this paper, we propose a novel gait recognition method based on a bag-of-gait model. In the proposed method, the image sequence of a walking person is encoded by a codebook consisting of a list of code words denoting different walking stages; then, this image sequence is represented by a feature vector denoting the existence of the code words, which is further used for classification. Unlike most of previous gait recognition methods, there is no need to estimate gait period in the proposed method. Moreover, the proposed method is capable of recognizing the gait when the observed gait period is incomplete which caused by occlusion or short appearance time. The method is evaluated on a dataset consisting of 151 subjects with four different walking conditions using four-fold cross-validation. The result shows the effectiveness of the proposed method and the state-of-art result is achieved on that dataset.-
dc.languageeng-
dc.publisherCSREA Press.-
dc.relation.ispartofProceedings of the 2012 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2012-
dc.titleA Bag-of-Gait Model for Gait Recognition-
dc.typeConference_Paper-
dc.identifier.emailChung, RHY: hychung@cs.hku.hk-
dc.identifier.emailChow, KP: kpchow@hkucc.hku.hk-
dc.identifier.authorityChung, RHY=rp00219-
dc.identifier.authorityChow, KP=rp00111-
dc.identifier.scopuseid_2-s2.0-84873281252-
dc.identifier.hkuros257372-
dc.identifier.volume2-
dc.identifier.spage871-
dc.identifier.epage876-
dc.publisher.placeLas Vegas, Nevada-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats