Classification and mapping of urban canyon geometry using Google Street View images and deep multitask learning
نویسندگان
چکیده
منابع مشابه
Urban Land Use Information Retrieval Based on Scene Classification of Google Street View Images
Land use maps are very important references for the urban planning and management. However, it is difficult and time-consuming to get high-resolution urban land use maps. In this study, we propose a new method to derive land use information at building block level based on machine learning and geo-tagged street-level imagery – Google Street View images. Several commonly used generic image featu...
متن کاملUsing Deep Learning and Google Street View to Estimate the Demographic Makeup of the US
The United States spends more than $1B each year on initiatives such as the Amer-ican Community Survey (ACS), a labor-intensive door-to-door study that measures demographic factors 1. Although a comprehensive source of data, the lag between demographic changes and their appearance in the ACS can exceed half a decade. As digital imagery becomes ubiquitous and machine vision techniques improve, a...
متن کاملBuilding Instance Classification Using Street View Images
This is the pre-print version, to read the final version please go to ISPRS Journal of Photogrammetry and Remote Sensing, Elsevier. (https://doi.org/DOI: 10.1016/j.isprsjprs.2018.02.006). Land-use classification based on spaceborne or aerial remote sensing images has been extensively studied over the past decades. Such classification is usually a patch-wise or pixel-wise labeling over the whole...
متن کاملGoogle Street View and Privacy
The Google Street View technology has proven to be highly controversial. Especially in a lot of European countries – where privacy and data protection laws are far stricter than e.g. in the United States – the launch of Street View has caused many residents and citizens to issues complaints to government officials about the project thereby claiming that it is a massive intrusion upon privacy an...
متن کاملUrban street mapping using Quickbird and Ikonos images
This article addresses the problem of urban street mapping from new high resolution satellite images. The proposed algorithm is divided in two sequential modules: a topologically correct graph of the street network is first extracted, and streets are then extracted as surface elements. The graph of the network is extracted by a following algorithm which minimizes a cost function. The surface ex...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Building and Environment
سال: 2020
ISSN: 0360-1323
DOI: 10.1016/j.buildenv.2019.106424