Building detection from orthophotos using a machine learning approach: An empirical study on image segmentation and descriptors
作者：
Highlights：
• Automatic building detection in orthophotos via a machine learning approach.
• Flexible framework that exploits supervised learning.
• Applying the covariance descriptor to the building detection problem.
• An extended performance study of several combination segmentation-descriptor.
• Classification performance is obtained with K-NN, Partial Least Square and SVM.
摘要
•Automatic building detection in orthophotos via a machine learning approach.•Flexible framework that exploits supervised learning.•Applying the covariance descriptor to the building detection problem.•An extended performance study of several combination segmentation-descriptor.•Classification performance is obtained with K-NN, Partial Least Square and SVM.
论文关键词：Automatic building detection and delineation,Orthophotos,Image segmentation,Image descriptors,Supervised learning,Classifier
论文评审过程：Received 22 May 2015, Revised 10 March 2016, Accepted 11 March 2016, Available online 31 March 2016, Version of Record 17 April 2016.
论文官网地址：https://doi.org/10.1016/j.eswa.2016.03.024
