Journal ArticleDOI
Object extraction and revision by image analysis using existing geodata and knowledge: current status and steps towards operational systems☆
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TLDR
In spite of many remaining unsolved problems and need for further research and development, use of knowledge and semi-automation are the only viable alternatives towards development of useful object extraction systems, as some commercial systems on building extraction and 3D city modelling as well as advanced, practically oriented research have shown.Abstract:
The paper focuses mainly on extraction of important topographic objects, like buildings and roads, that have received much attention the last decade. As main input data, aerial imagery is considered, although other data, like from laser scanner, SAR and high-resolution satellite imagery, can be also used. After a short review of recent image analysis trends, and strategy and overall system aspects of knowledge-based image analysis, the paper focuses on aspects of knowledge that can be used for object extraction: types of knowledge, problems in using existing knowledge, knowledge representation and management, current and possible use of knowledge, upgrading and augmenting of knowledge. Finally, an overview on commercial systems regarding automated object extraction and use of a priori knowledge is given. In spite of many remaining unsolved problems and need for further research and development, use of knowledge and semi-automation are the only viable alternatives towards development of useful object extraction systems, as some commercial systems on building extraction and 3D city modelling as well as advanced, practically oriented research have shown.read more
Citations
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Journal ArticleDOI
Object based image analysis for remote sensing
TL;DR: This paper gives an overview of the development of object based methods, which aim to delineate readily usable objects from imagery while at the same time combining image processing and GIS functionalities in order to utilize spectral and contextual information in an integrative way.
Journal ArticleDOI
A survey on object detection in optical remote sensing images
Gong Cheng,Junwei Han +1 more
TL;DR: This survey focuses on more generic object categories including, but not limited to, road, building, tree, vehicle, ship, airport, urban-area, and proposes two promising research directions, namely deep learning- based feature representation and weakly supervised learning-based geospatial object detection.
Journal ArticleDOI
Distributed solar photovoltaic array location and extent dataset for remote sensing object identification.
Kyle Bradbury,Raghav Saboo,Timothy L. Johnson,Jordan M. Malof,Arjun Devarajan,Wuming Zhang,Leslie M. Collins,Richard G. Newell +7 more
TL;DR: This work created a dataset of solar PV arrays to initiate and develop the process of automatically identifying solar PV locations using remote sensing imagery, and contains the geospatial coordinates and border vertices for over 19,000 solar panels across 601 high-resolution images from four cities in California.
Book ChapterDOI
Learning to detect roads in high-resolution aerial images
TL;DR: This work proposes detecting roads using a neural network with millions of trainable weights which looks at a much larger context than was used in previous attempts at learning the task, and shows that the method works reliably on two challenging urban datasets that are an order of magnitude larger than what was used to evaluate previous approaches.
References
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A framework for representing knowledge
TL;DR: The enormous problem of the volume of background common sense knowledge required to understand even very simple natural language texts is discussed and it is suggested that networks of frames are a reasonable approach to represent such knowledge.
A framework for representing knowledge
TL;DR: The authors describes frame systems as a formalism for representing knowledge and then concentrates on the issue of what the content of knowledge should be in specific domains, arguing that vision should be viewed symbolically with an emphasis on forming expectations and then using details to fill in slots in those expectations.