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Article

Automatic Discovery and Geotagging of Objects from Street View Imagery

ADAPT Centre, School of Computer Science and Statistics, Trinity College Dublin, Dublin 2, Ireland
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Remote Sens. 2018, 10(5), 661; https://doi.org/10.3390/rs10050661
Received: 9 March 2018 / Revised: 9 April 2018 / Accepted: 18 April 2018 / Published: 24 April 2018
(This article belongs to the Special Issue Multisensor Data Fusion in Remote Sensing)
Many applications, such as autonomous navigation, urban planning, and asset monitoring, rely on the availability of accurate information about objects and their geolocations. In this paper, we propose the automatic detection and computation of the coordinates of recurring stationary objects of interest using street view imagery. Our processing pipeline relies on two fully convolutional neural networks: the first segments objects in the images, while the second estimates their distance from the camera. To geolocate all the detected objects coherently we propose a novel custom Markov random field model to estimate the objects’ geolocation. The novelty of the resulting pipeline is the combined use of monocular depth estimation and triangulation to enable automatic mapping of complex scenes with the simultaneous presence of multiple, visually similar objects of interest. We validate experimentally the effectiveness of our approach on two object classes: traffic lights and telegraph poles. The experiments report high object recall rates and position precision of approximately 2 m, which is approaching the precision of single-frequency GPS receivers.
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Keywords: object geolocation; object mapping; street view imagery; Markov random fields; traffic lights; telecom assets; GPS estimation object geolocation; object mapping; street view imagery; Markov random fields; traffic lights; telecom assets; GPS estimation
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MDPI and ACS Style

Krylov, V.A.; Kenny, E.; Dahyot, R. Automatic Discovery and Geotagging of Objects from Street View Imagery. Remote Sens. 2018, 10, 661. https://doi.org/10.3390/rs10050661

AMA Style

Krylov VA, Kenny E, Dahyot R. Automatic Discovery and Geotagging of Objects from Street View Imagery. Remote Sensing. 2018; 10(5):661. https://doi.org/10.3390/rs10050661

Chicago/Turabian Style

Krylov, Vladimir A., Eamonn Kenny, and Rozenn Dahyot. 2018. "Automatic Discovery and Geotagging of Objects from Street View Imagery" Remote Sensing 10, no. 5: 661. https://doi.org/10.3390/rs10050661

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