People Re-identification with Auxiliary Knowledge

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概要

• 論文の詳細を見る

• There is an intrinsic issue in multiple-shot person re-identification: only a few training data for learning tasks are available in a realistic re-identification scenario. A novel adaptive metric learning method is introduced in this paper for multiple-shot people re-identification. By leveraging the auxiliary knowledge of re-identification together with the specific information of the target task, the proposed adaptive learning method is able to solve over-fitting problem caused by limited training data. We evaluated our approach on public benchmark datasets, and confirmed its superiority as compared to conventional approaches.

• 一般社団法人電子情報通信学会の論文
• 2014-01-16

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.

• Zhang Guanwen

  Graduate School of Information Science, Nagoya University

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