People Re-identification Using Local Similarity Estimation (パターン認識・メディア理解)

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概要

• 論文の詳細を見る

• In this paper, we propose an efficient and robust approach for multiple-shot people re-identification. To compare the people's appearance instances of image set, we explore the multimodal property of people appearance distribution and estimate the similarity in the local neighbours of the appearance instances. An energy-based loss function is proposed to measure the distance as the similarity in feature space. This loss function favors close distances to support the people with high similarity and penalizes large distances as well as overlap between neighbours to exclude the people with low similarity. Experiments on the public datasets show significant improvements over previous reports.

• 一般社団法人電子情報通信学会の論文
• 2012-09-27

著者

• Wang Yu

  Graduate Institute Of Natural Products College Of Medicine Chang Gung University

• Mase Kenji

  Graduate School Of Information Science Nagoya University

• Kato Jien

  Graduate School Of Information Sci. Nagoya Univ.

• Wang Yu

  Graduate School of Information Science, Nagoya University

• Zhang Guanwen

  Graduate School of Information Science, Nagoya University

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