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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPBW34M/3C92QTP
Repositorysid.inpe.br/sibgrapi/2012/07.10.00.53
Last Update2012:07.10.00.53.06 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2012/07.10.00.53.06
Metadata Last Update2022:06.14.00.07.25 (UTC) administrator
DOI10.1109/SIBGRAPI.2012.20
Citation KeySilvaFoSchnOliv:2012:MuSpRe
TitleMulti-Scale Spectral Residual Analysis to Speed up Image Object Detection
FormatDVD, On-line.
Year2012
Access Date2024, May 04
Number of Files1
Size4541 KiB
2. Context
Author1 Silva Filho, José Grimaldo da
2 Schnitman, Leizer
3 Oliveira, Luciano Rebouças de
Affiliation1 Universidade Federal da Bahia 
2 Universidade Federal da Bahia 
3 Universidade Federal da Bahia
EditorFreitas, Carla Maria Dal Sasso
Sarkar, Sudeep
Scopigno, Roberto
Silva, Luciano
e-Mail Addressjose.jgrimaldo@gmail.com
Conference NameConference on Graphics, Patterns and Images, 25 (SIBGRAPI)
Conference LocationOuro Preto, MG, Brazil
Date22-25 Aug. 2012
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2012-09-20 16:45:34 :: jose.jgrimaldo@gmail.com -> administrator :: 2012
2022-03-08 21:03:23 :: administrator -> menottid@gmail.com :: 2012
2022-03-10 13:04:26 :: menottid@gmail.com -> administrator :: 2012
2022-06-14 00:07:25 :: administrator -> :: 2012
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
Keywordsmulti-scale spectral residue
saliency
person detection
AbstractAccuracy in image object detection has been usually achieved at the expense of much computational load. Therefore a trade-off between detection performance and fast execution commonly represents the ultimate goal of an object detector in real life applications. In this present work, we propose a novel method toward that goal. The proposed method was grounded on a multi-scale spectral residual (MSR) analysis for saliency detection. Compared to a regular sliding window search over the images, in our experiments, MSR was able to reduce by 75% (in average) the number of windows to be evaluated by an object detector. The proposed method was thoroughly evaluated over a subset of LabelMe dataset (person images), improving detection performance in most cases.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2012 > Multi-Scale Spectral Residual...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Multi-Scale Spectral Residual...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPBW34M/3C92QTP
zipped data URLhttp://urlib.net/zip/8JMKD3MGPBW34M/3C92QTP
Languageen
Target FilePID2440145.pdf
User Groupjose.jgrimaldo@gmail.com
Visibilityshown
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/46SL8GS
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2022/05.15.03.31 6
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage 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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