A theoretical justification of warping generation for dewarping using CNN

作者：

Highlights：

• A mathematical model for warping generation is proposed.

• The model uses geometric parameters like the camera angle, camera position, distance from the object to camera and curvature the surface to generate warping.

• Synthetic images are generated using the model.

• Value of the geometric parameters is estimated using CNN from a 2D warped image.

• Performances of both the synthetic image generation and dewarping model are analysed.

摘要

•A mathematical model for warping generation is proposed.•The model uses geometric parameters like the camera angle, camera position, distance from the object to camera and curvature the surface to generate warping.•Synthetic images are generated using the model.•Value of the geometric parameters is estimated using CNN from a 2D warped image.•Performances of both the synthetic image generation and dewarping model are analysed.

论文关键词：Dewarping,Artificial neural netwroks,Synthetic image generation

论文评审过程：Received 10 February 2020, Revised 21 August 2020, Accepted 29 August 2020, Available online 30 August 2020, Version of Record 1 September 2020.

论文官网地址：https://doi.org/10.1016/j.patcog.2020.107621