Bag of shape descriptor using unsupervised deep learning for non-rigid shape recognition

作者：

Highlights：

• Our method is specially designed to learn high-level and hierarchical shape features from multi-scale context structures.

• An improved decomposing strategy is redesigned to generate valuable contour fragments, results in local to global feature learning.

• An unsupervised learning framework is also applied to the contour fragment for its feature expression based on the context structure and SSAE (Stack Sparse Auto Encode).

摘要

•Our method is specially designed to learn high-level and hierarchical shape features from multi-scale context structures.•An improved decomposing strategy is redesigned to generate valuable contour fragments, results in local to global feature learning.•An unsupervised learning framework is also applied to the contour fragment for its feature expression based on the context structure and SSAE (Stack Sparse Auto Encode).

论文关键词：Shape recognition,Bag of shape descriptor,Unsupervised deep learning,High-level feature dictionary,Shape coding

论文评审过程：Received 9 November 2020, Revised 22 January 2021, Accepted 16 April 2021, Available online 20 April 2021, Version of Record 6 May 2021.

论文官网地址：https://doi.org/10.1016/j.image.2021.116297