Building instance segmentation and boundary regularization from high-resolution remote sensing images

Research output: Contribution to conferencePaperAcademicpeer-review

Abstract

Building extraction from remote sensing images using convolutional neural networks (CNNs) has been an active research topic in recent years. Most results obtained by CNN-based algorithms, however, still have common issues with the precision of the delineation of building outlines and the separation of different buildings. Recently, efforts have been made towards the automation of building outline regularization. This paper employs a new instance segmentation framework named Hybrid Task Cascade (HTC) as baseline model, integrating detection and segmentation as a joint multi-stage processing. We further integrate regularization methods such as convex hull and Douglas-Peucker algorithm to obtain accurately segmented edges. The method is tested on the crowdAI benchmark dataset by comparing with alternative state-of-the-art models (i.e., Mask R-CNN). The results show that our method achieves better instance segmentation results and improves the results in terms of geometric regularity of building segments. © 2020 IEEE.
Original languageEnglish
Pages3916-3919
Number of pages4
DOIs
Publication statusPublished - 2020
Event2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020 - Virtual, Waikoloa, United States
Duration: 26 Sep 20202 Oct 2020

Conference

Conference2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020
CountryUnited States
CityVirtual, Waikoloa
Period26/09/202/10/20

Keywords

  • Boundary Regularization
  • Building Extraction
  • Instance Segmentation
  • Buildings
  • Convolutional neural networks
  • Geology
  • Image segmentation
  • Object recognition
  • Building extraction
  • Douglas-peucker algorithm
  • Geometric regularity
  • High resolution remote sensing images
  • Multi-stage processing
  • Regularization methods
  • Remote sensing images
  • Segmentation results
  • Remote sensing

Fingerprint Dive into the research topics of 'Building instance segmentation and boundary regularization from high-resolution remote sensing images'. Together they form a unique fingerprint.

Cite this