Fast medium-scale multiperson identification in aerial videos

Mei Chen Yeh*, Han Kuen Chiu, Jia Shung Wang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)


Vision systems for unmanned aerial vehicles (UAVs) have been gaining increasing attention for surveillance and civil applications. However, aerial platforms create new challenges for several vision tasks (e.g., human tracking and identification) because UAV-mounted cameras undergo large vibration movements and capture unstable videos. Furthermore, most existing machine vision approaches use the fine details of a human figure, which are unavailable in low-quality aerial images. We propose a new blob-matching approach for human identification in aerial videos in which the identity of a human blob is estimated using an adaptive reference set of previously identified people. A target can be quickly located by matching only the target and a carefully selected candidate set. The experimental results obtained using several challenging aerial videos validated the effectiveness and computational efficiency of the proposed method.

Original languageEnglish
Pages (from-to)16117-16133
Number of pages17
JournalMultimedia Tools and Applications
Issue number23
Publication statusPublished - 2016 Dec 1


  • Aerial video
  • Human identity recognition
  • Image matching
  • Video surveillance

ASJC Scopus subject areas

  • Software
  • Media Technology
  • Hardware and Architecture
  • Computer Networks and Communications


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