Multiple instance subspace learning via partial random projection tree for local reflection symmetry in natural images

作者：

Highlights：

• We perform clustering on samples represented by multiple instances.

• We learn a group of MIL classifiers on subspaces.

• We report state-of-the-arts results on the symmetry detection benchmark.

摘要

Highlights•We perform clustering on samples represented by multiple instances.•We learn a group of MIL classifiers on subspaces.•We report state-of-the-arts results on the symmetry detection benchmark.

论文关键词：Symmetry detection,Multiple instance subspace learning,Partial random projection tree

论文评审过程：Received 26 February 2015, Revised 14 July 2015, Accepted 19 October 2015, Available online 6 November 2015, Version of Record 24 December 2015.

论文官网地址：https://doi.org/10.1016/j.patcog.2015.10.015