跳至主導覽 跳至搜尋 跳過主要內容

Robust local effective matching model for multi-target tracking

  • Hao Sheng
  • , Li Hao
  • , Jiahui Chen
  • , Yang Zhang
  • , Wei Ke

研究成果: Conference contribution同行評審

7 引文 斯高帕斯(Scopus)

摘要

Occlusion is one of the main challenges in multi-target tracking, which causes fragments in tracking. In order to handle with fragments, various motion models were proposed. However, motion model has limited effect on dealing with long-term fragments, because the predictability of target motion declines with increase in fragment length. Thus we propose a robust local effective matching model for partial detections to reduce fragment length first. The proposed model is integrated into a network flow based hierarchical framework to solve long-term fragments step-by-step. Initial tracklets are generated for later analysis in the first level. The robust local effective matching model is used in the second level to reduce fragment length. A motion model is utilized in the third level to solve fragments between tracklets. The benchmark results on 2D MOT 2015 dataset were compared with several state-of-the-art trackers and our method got competitive results with those trackers.

原文English
主出版物標題Advances in Multimedia Information Processing – PCM 2017 - 18th Pacific-Rim Conference on Multimedia, Revised Selected Papers
編輯Bing Zeng, Hongliang Li, Qingming Huang, Abdulmotaleb El Saddik, Shuqiang Jiang, Xiaopeng Fan
發行者Springer Verlag
頁面233-243
頁數11
ISBN(列印)9783319773827
DOIs
出版狀態Published - 2018
事件18th Pacific-Rim Conference on Multimedia, PCM 2017 - Harbin, China
持續時間: 28 9月 201729 9月 2017

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
10736 LNCS
ISSN(列印)0302-9743
ISSN(電子)1611-3349

Conference

Conference18th Pacific-Rim Conference on Multimedia, PCM 2017
國家/地區China
城市Harbin
期間28/09/1729/09/17

指紋

深入研究「Robust local effective matching model for multi-target tracking」主題。共同形成了獨特的指紋。

引用此