Deep feature learning with relative distance comparison for person re-identification

作者：

Highlights：

• We present a novel feature learning framework for person re-identification.

• Our framework is based on the maximum relative distance comparison.

• The learning algorithm is scalable to process large amount of data.

• We demonstrate superior performances over other state-of-the-arts.

摘要

Highlights•We present a novel feature learning framework for person re-identification.•Our framework is based on the maximum relative distance comparison.•The learning algorithm is scalable to process large amount of data.•We demonstrate superior performances over other state-of-the-arts.

论文关键词：Person re-identification,Deep learning,Distance comparison

论文评审过程：Received 28 September 2014, Revised 28 February 2015, Accepted 2 April 2015, Available online 17 April 2015, Version of Record 17 June 2015.

论文官网地址：https://doi.org/10.1016/j.patcog.2015.04.005