Robust identification of fiducial markers in challenging conditions

作者：

Highlights：

• This work tackles the marker identification process as a classification problem.

• Methodology proposed to train the classifiers with a synthetic dataset of markers.

• Our proposal can identify markers under very difficult image conditions.

• The proposed method performs significantly better than previous approaches.

摘要

•This work tackles the marker identification process as a classification problem.•Methodology proposed to train the classifiers with a synthetic dataset of markers.•Our proposal can identify markers under very difficult image conditions.•The proposed method performs significantly better than previous approaches.

论文关键词：Fiducial markers,Augmented reality,Machine learning,Convolutional neural networks,Support vector machines,Multilayer perceptron

论文评审过程：Received 8 May 2017, Revised 29 September 2017, Accepted 12 October 2017, Available online 16 October 2017, Version of Record 5 November 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.10.032