Close
Metadata

1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPBW34M/3CA2RQE
Repositorysid.inpe.br/sibgrapi/2012/07.16.04.41
Last Update2012:07.16.21.14.21 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2012/07.16.04.41.01
Metadata Last Update2022:06.14.00.07.37 (UTC) administrator
DOI10.1109/SIBGRAPI.2012.40
Citation KeyLeónHira:2012:StDyCa
TitleVehicle Detection using Mixture of Deformable Parts Models: Static and Dynamic Camera
FormatDVD, On-line.
Year2012
Access Date2024, Apr. 27
Number of Files1
Size10755 KiB
2. Context
Author1 León, Leissi Margarita Castañeda
2 Hirata Junior, Roberto
Affiliation1 Institute of Mathematics and Statistics 
2 Institute of Mathematics and Statistics
EditorFreitas, Carla Maria Dal Sasso
Sarkar, Sudeep
Scopigno, Roberto
Silva, Luciano
e-Mail Addressleissicl@ime.usp.br
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 :: leissicl@ime.usp.br -> administrator :: 2012
2022-03-08 21:03:25 :: administrator -> menottid@gmail.com :: 2012
2022-03-10 12:58:17 :: menottid@gmail.com -> administrator :: 2012
2022-06-14 00:07:37 :: administrator -> :: 2012
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
KeywordsMixture of deformable part models
vehicle detection
AbstractVehicle detection in video is an important problem in Computer Vision because of the potential applications in security, vehicle traffic, driving assistance and so on. In this work, we used Mixture of Deformable Part Models (MDPM) for vehicle detection in video sequences obtained from static and dynamic cameras. The MDPM method was originally proposed by Felzenszwalb et al in the realm of object detection in images. We tested this method in the realm of video sequences for vehicle detection. We designed a set of experiments that explore the number of components of the mixture and the number of parts model. We performed a comparison study of symmetric and asymmetric MDPMs for vehicle detection. Our findings show that not only the MDPM performed well in vehicle detection in video, but also the best number of components and parts model confirmed the number suggested in Felzenzwalb et al's paper. Finally, the results show some differences between the symmetric and asymmetric MDPMs in vehicle video detection considering different scenarios.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2012 > Vehicle Detection using...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Vehicle Detection using...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
agreement.html 16/07/2012 01:41 0.7 KiB 
4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPBW34M/3CA2RQE
zipped data URLhttp://urlib.net/zip/8JMKD3MGPBW34M/3CA2RQE
Languageen
Target FilePID2451827.pdf
User Groupleissicl@ime.usp.br
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 5
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


Close