Object extraction and revision by image analysis using existing geodata and knowledge: current status and steps towards operational systems☆

By Emmanuel Baltsavias. 2004

323 citations recorded by the source corpus.

Subfields: Environmental Engineering, Media Technology, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/db59301f3686ca6aa057a950566fe69bcac36d06

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In Environmental Engineering

In Media Technology

In Ocean Engineering

Citations in the corpus

An update on automatic 3D building reconstruction (2010, unknown): “In this article, we want to focus primarily on the developments of the last couple of years with the purpose to close the gap between today and the thorough overviews given by Brenner (2005) and Baltsavias (2004) and the EuroSDR project on building extraction (Kaartinen and Hyyppä, 2006).”
Object based image analysis for remote sensing (2010, background): “, 2006; Navulur, 2007; Lang, 2008; Hay and Castilla, 2008) that OBIA builds on older segmentation, edge-detection, feature extraction and classification concepts that have been used in remote sensing image analysis for decades (Kettig and Landgrebe, 1976; Haralick, 1983; Haralick and Shapiro, 1985; ”
Advances in fusion of optical imagery and LiDAR point cloud applied to photogrammetry and remote sensing (2017, methodology): “Most existing road extraction methods from images (Mena 2003, Baltsavias 2004, Shi et al. 2014) still suffer from the abrupt irregular geometric deformations and radiometric changes due to appearance of road junctions, material change, traffic jams, shadows of trees and tall buildings, road…”
A Survey on Object Detection in Optical Remote Sensing Images (2016, unknown): “l, 2008; Janssen and Middelkoop, 1992; Martha et al., 2011; Moon et al., 2002; Solberg, 1999; Tchoku et al., 1996; Wang, 1993). A review of knowledge-based object extraction in RSIs is also given in (Baltsavias, 2004). This type of approaches generally translates object detection problem into hypoth”
Machine Learning for Aerial Image Labeling (2013, background): “While significant progress has been made in the past thirty years, only a few semi-automated systems that work in limited domains are in use today and no fully automated systems currently exist [Baltsavias, 2004, Mayer, 2008].”
Learning to Detect Roads in High-Resolution Aerial Images (2010, background): “Nevertheless, despite over 30 years of effort [1], at the time of writing there was no commercial automatic or semi-automatic road detection system on the market [2, 3] and, to the best of our knowledge, no published method has been shown to work reliably on large datasets of high-resolution urban i”