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Fast medium-scale multiperson identification in aerial videos

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Abstract

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.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Information Engineering, National Taiwan Normal University, Taipei, Taiwan

    Mei-Chen Yeh

  2. Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan

    Han-Kuen Chiu & Jia-Shung Wang

Authors
  1. Mei-Chen Yeh
  2. Han-Kuen Chiu
  3. Jia-Shung Wang

Corresponding author

Correspondence toMei-Chen Yeh.

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Yeh, MC., Chiu, HK. & Wang, JS. Fast medium-scale multiperson identification in aerial videos.Multimed Tools Appl75, 16117–16133 (2016). https://doi.org/10.1007/s11042-015-2921-x

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