Tracking People in Dense Crowds Using Supervoxels

Shota Takayama, Teppei Suzuki, Yoshimitsu Aoki, Sho Isobe, Makoto Masuda

研究成果: Conference contribution

抄録

The demand for people tracking in dense crowds is increasing, but it is a challenging problem in the computer vision field. 'Crowd tracking' is extremely difficult because of hard occlusions, various motions and posture changes. In particular, we need to handle occlusions for more robust tracking. This paper discusses robust crowd tracking based on a combination of supervoxels and optical flow tracking. The SLIC based supervoxel algorithm adaptively estimates the boundary between a person and a background. Therefore, the combination of supervoxels and optical flow tracking becomes a highly reliable approach for crowd tracking. In tracking experiments, high performance is achieved for the UCF crowd dataset.

本文言語English
ホスト出版物のタイトルProceedings - 12th International Conference on Signal Image Technology and Internet-Based Systems, SITIS 2016
出版社Institute of Electrical and Electronics Engineers Inc.
ページ532-537
ページ数6
ISBN(電子版)9781509056989
DOI
出版ステータスPublished - 2017 4月 21
イベント12th International Conference on Signal Image Technology and Internet-Based Systems, SITIS 2016 - Naples, Italy
継続期間: 2016 11月 282016 12月 1

Other

Other12th International Conference on Signal Image Technology and Internet-Based Systems, SITIS 2016
国/地域Italy
CityNaples
Period16/11/2816/12/1

ASJC Scopus subject areas

  • コンピュータ ビジョンおよびパターン認識
  • 放射線学、核医学およびイメージング
  • コンピュータ ネットワークおよび通信
  • 信号処理

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