Particle filter tracking in low frame rate video

Object tracking algorithm using modified Particle filter in low frame rate (LFR) video is proposed in this paper, which the object moving significantly and randomly between consecutive frames in the low frame rate situation. Traditionally, Particle filtering use motion transitions to model the movem...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Proceedings of the 30th Chinese Control Conference s. 3254 - 3259
Hlavní autoři: Zhang Tao, Fei Shumin, Wang Lili
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.07.2011
Témata:
Detection
Heuristic algorithms
Histograms
Image color analysis
Low Frame Rate
Noise
Object Tracking
Particle filter
Particle filters
Target tracking
ISBN:9781457706776, 1457706776
ISSN:1934-1768
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Abstract Object tracking algorithm using modified Particle filter in low frame rate (LFR) video is proposed in this paper, which the object moving significantly and randomly between consecutive frames in the low frame rate situation. Traditionally, Particle filtering use motion transitions to model the movement of the target. However, in object tracking with low frame rate sequences, it is very difficult to model significant random jumps of subjects. The key notion of our solution is that using the object detection and extraction to locate the tracked object, while not using the dynamical function. We propagate the sample set around the detected regions, which the samples are assumed to be uniformly distributed in the neighborhoods of the detected region. It is similar to the general particle filter to propagate samples. Then we compute the likelihood between the target model and the candidate regions, which are based on color histogram distances. Our extensive experiments show that the proposed algorithm performs robustly in a large variety of tracking scenarios..
AbstractList Object tracking algorithm using modified Particle filter in low frame rate (LFR) video is proposed in this paper, which the object moving significantly and randomly between consecutive frames in the low frame rate situation. Traditionally, Particle filtering use motion transitions to model the movement of the target. However, in object tracking with low frame rate sequences, it is very difficult to model significant random jumps of subjects. The key notion of our solution is that using the object detection and extraction to locate the tracked object, while not using the dynamical function. We propagate the sample set around the detected regions, which the samples are assumed to be uniformly distributed in the neighborhoods of the detected region. It is similar to the general particle filter to propagate samples. Then we compute the likelihood between the target model and the candidate regions, which are based on color histogram distances. Our extensive experiments show that the proposed algorithm performs robustly in a large variety of tracking scenarios..
Author Zhang Tao
Wang Lili
Fei Shumin
Author_xml – sequence: 1
  surname: Zhang Tao
  fullname: Zhang Tao
  email: tzhangcn@gmail.com
  organization: Coll. of Autom. Electron. Eng., Qingdao Univ. of Sci. & Technol., Qingdao, China
– sequence: 2
  surname: Fei Shumin
  fullname: Fei Shumin
  email: smfei@seu.edu.cn
  organization: Sch. of Autom., Southeast Univ., Nanjing, China
– sequence: 3
  surname: Wang Lili
  fullname: Wang Lili
  email: wll_bupt@yahoo.com.cn
  organization: Coll. of Autom. Electron. Eng., Qingdao Univ. of Sci. & Technol., Qingdao, China
BookMark eNotzMtKAzEUANCIFey0_QI3-YGB3CSTmyyl-IKCLnRd8rgp0emMZILi37vQ1dmdjq2meaIL1jlrAeUwOHXJdg4t6AFRGESzYmtwSveAxl6zblnehTDCgVoz8eJrK3EknsvYqPJWffwo04mXiY_zN8_Vn4lX34h_lUTzll1lPy60-3fD3u7vXveP_eH54Wl_e-gLiKH1IUXnUSJSVhg9EUiTXSClpZPaY9IopU8BdYg5SWcy2YQiBUsSbAK1YTd_byGi42ctZ19_jkYI0ADqF150QsQ
ContentType Conference Proceeding
DBID 6IE
6IL
CBEJK
RIE
RIL
DatabaseName IEEE Electronic Library (IEL) Conference Proceedings
IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume
IEEE Xplore All Conference Proceedings
IEEE Electronic Library (IEL)
IEEE Proceedings Order Plans (POP All) 1998-Present
DatabaseTitleList
Database_xml – sequence: 1
  dbid: RIE
  name: IEEE Electronic Library (IEL)
  url: https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
Discipline Engineering
EISBN 9881725593
9789881725592
EndPage 3259
ExternalDocumentID 6001411
Genre orig-research
GroupedDBID 29B
6IE
6IF
6IK
6IL
6IN
AAJGR
AAWTH
ABLEC
ACGFS
ADZIZ
ALMA_UNASSIGNED_HOLDINGS
BEFXN
BFFAM
BGNUA
BKEBE
BPEOZ
CBEJK
CHZPO
IEGSK
IPLJI
M43
OCL
RIE
RIL
ID FETCH-LOGICAL-i105t-bdc9a7277ef37caee126f9be342924a7d4722adb74bcfd296fe8d70db8e218d13
IEDL.DBID RIE
ISBN 9781457706776
1457706776
ISICitedReferencesCount 0
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000312652103074&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN 1934-1768
IngestDate Wed Aug 27 03:25:27 EDT 2025
IsPeerReviewed false
IsScholarly true
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-i105t-bdc9a7277ef37caee126f9be342924a7d4722adb74bcfd296fe8d70db8e218d13
PageCount 6
ParticipantIDs ieee_primary_6001411
PublicationCentury 2000
PublicationDate 2011-July
PublicationDateYYYYMMDD 2011-07-01
PublicationDate_xml – month: 07
  year: 2011
  text: 2011-July
PublicationDecade 2010
PublicationTitle Proceedings of the 30th Chinese Control Conference
PublicationTitleAbbrev CHICC
PublicationYear 2011
Publisher IEEE
Publisher_xml – name: IEEE
SSID ssj0060913
ssj0000669033
Score 1.765468
Snippet Object tracking algorithm using modified Particle filter in low frame rate (LFR) video is proposed in this paper, which the object moving significantly and...
SourceID ieee
SourceType Publisher
StartPage 3254
SubjectTerms Detection
Heuristic algorithms
Histograms
Image color analysis
Low Frame Rate
Noise
Object Tracking
Particle filter
Particle filters
Target tracking
Title Particle filter tracking in low frame rate video
URI https://ieeexplore.ieee.org/document/6001411
WOSCitedRecordID wos000312652103074&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3NS8MwFH_M4UEvfmziNzl4tLo0bdKexeFBxg4qu418vEBBWpmd_vvmpdtU8OItDRQaGvJe3u_jAVzlpdSYhWuJ5yJPMsd1YpCXSa697KC72Drh5VFNJsVsVk57cL3RwiBiJJ_hDQ0jlu8au6RS2a2MtMRw19lSSnZarU09JYTOMiJy3Sksye-yQ5QzMkEsoqgrV4oc0-Ta62n9_Ku1Sows473_fdM-DL8lemy6CT4H0MP6EHZ_uAsOYDRdbQvmK8LEWbvQlirjrKrZa_PJPBGzGHlFMFLjNUN4Ht8_3T0kqwYJSRXSojYxzpY6JCAKvVBWI_JU-tKgoB5UmVaOnCC1Myoz1ru0lB4Lp0bOFBgiu-PiCPp1U-MxMEmcTOW4FcKHHKUIWUSKnJsivJeOBJ7AgNY-f-s8MOarZZ_-PX0GO13tlWit59BvF0u8gG370Vbvi8v4474AupaTxQ
linkProvider IEEE
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3NS8MwFH-MKagXPzbx2xw8Wl36kTRncUycY4cpu420eYGCtDI7_ffNS7ep4MVbW2hoSMl7eb-PB3CVKKExdscSy6MkiA3XQYZcBYm2ooHufOuEl6EcjdLpVI1bcL3WwiCiJ5_hDV16LN9U-YJKZbfC0xLdWWcjid34jVprXVFxwVN5TK7ZhwU5XjaYckw2iKmXdSVSkmeaWLk9re5_NVfxsaW_-7-v2oPut0iPjdfhZx9aWB7Azg9_wQ70xssfg9mCUHFWz3VOtXFWlOy1-mSWqFmM3CIY6fGqLjz37yd3g2DZIiEoXGJUB5nJlXYpiEQbyVwj8lBYlWFEXahiLQ15QWqTyTjLrQmVsJga2TNZii62Gx4dQrusSjwCJoiVKQ3Po8i6LCV1eUSInGepey_sRXgMHZr77K1xwZgtp33y9-NL2BpMnoaz4cPo8RS2m0oskVzPoF3PF3gOm_lHXbzPL_wifgGhcZcM
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=proceeding&rft.title=Proceedings+of+the+30th+Chinese+Control+Conference&rft.atitle=Particle+filter+tracking+in+low+frame+rate+video&rft.au=Zhang+Tao&rft.au=Fei+Shumin&rft.au=Wang+Lili&rft.date=2011-07-01&rft.pub=IEEE&rft.isbn=9781457706776&rft.issn=1934-1768&rft.spage=3254&rft.epage=3259&rft.externalDocID=6001411
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1934-1768&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1934-1768&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1934-1768&client=summon