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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPAW/3PHKBHE
Repositorysid.inpe.br/sibgrapi/2017/09.01.19.59
Last Update2017:09.01.19.59.43 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2017/09.01.19.59.43
Metadata Last Update2022:06.14.00.09.05 (UTC) administrator
DOI10.1109/SIBGRAPI.2017.26
Citation KeyAlmeidaJrGuim:2017:CaStHu
TitleA New Pooling Strategy based on Local Feature Distribution: A Case Study for Human Action Classification
FormatOn-line
Year2017
Access Date2025, July 08
Number of Files1
Size2501 KiB
2. Context
Author1 Almeida, Raquel
2 Jr, Zenilton K. Goncalves do Patrocinio
3 Guimaraes, Silvio Jamil Ferzoli
Affiliation1 PUC Minas
2 PUC Minas
3 PUC Minas
EditorTorchelsen, Rafael Piccin
Nascimento, Erickson Rangel do
Panozzo, Daniele
Liu, Zicheng
Farias, Mylène
Viera, Thales
Sacht, Leonardo
Ferreira, Nivan
Comba, João Luiz Dihl
Hirata, Nina
Schiavon Porto, Marcelo
Vital, Creto
Pagot, Christian Azambuja
Petronetto, Fabiano
Clua, Esteban
Cardeal, Flávio
e-Mail Addresssjamil@pucminas.br
Conference NameConference on Graphics, Patterns and Images, 30 (SIBGRAPI)
Conference LocationNiterói, RJ, Brazil
Date17-20 Oct. 2017
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2017-09-01 19:59:43 :: sjamil@pucminas.br -> administrator ::
2022-06-14 00:09:05 :: administrator -> :: 2017
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
KeywordsMid-level representation
Human action classification
Pooling
AbstractMid-level representations are used to map sets of local features into one global representation for a given media descriptor. In visual pattern recognition tasks, Bag-of-Words (BoW) is one popular strategy, among many methods available in literature, due mainly by the simplicity in concept and implementation. Despite the overall good results achieved by BoW in many tasks, the method is unstable in high dimensional feature space and quantization errors are usually ignored in the final representation. To cope with these problems, we propose a new pooling function based on feature points distribution around codewords. We propose to use the standard deviation associated with each codeword to measure attribution discrepancy and weight the impact that feature points will assume in the final representation. The main contribution of this article is the study of more discriminative representations, which amplify values of feature points close to codewords border regions. Experiments were conducted in human action classification task and results demonstrated that our pooling strategy has improved the classification rates in 25.6% for UCF Sports dataset and 21.4% for UCF 11 dataset, with respect to the original pooling function used in BoW.
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPAW/3PHKBHE
zipped data URLhttp://urlib.net/zip/8JMKD3MGPAW/3PHKBHE
Languageen
Target FilePID4982925.pdf
User Groupsjamil@pucminas.br
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPAW/3PKCC58
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2017/09.12.13.04 49
sid.inpe.br/sibgrapi/2022/06.10.21.49 5
sid.inpe.br/banon/2001/03.30.15.38.24 2
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url volume


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