People tracking in dense crowds using optical flow clustering based superpixel

Shota Takayama, Hirokatsu Kataoka, Sho Isobe, Naoki Kurita, Makoto Masuda, Yoshimitsu Aoki

研究成果: Article査読

抄録

People tracking in crowded scenes should be focused since the problem is beneficial and challenging in computer vision field. However, the problem of "crowd tracking" is extremely difficult because hard occlusions, various motions and posture changes. Especially in the crowd tracking, we need to handle occlusion for more robust tracking. This paper tackles a robust crowd tracking based on combination of superpixel and optical flow tracking. The SLIC based superpixel algorithm adaptively estimates a boundary between person and background, therefore the combination of superpixel and optical flow tracking becomes a highly confident tracking for crowd tracking. The tracking experiments show significant results on the UCF crowd dataset in terms of performance rate with comparison.

本文言語English
ページ(範囲)259-265
ページ数7
ジャーナルSeimitsu Kogaku Kaishi/Journal of the Japan Society for Precision Engineering
82
3
出版ステータスPublished - 2016

ASJC Scopus subject areas

  • 機械工学

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