Geocoding of trees from street addresses and street-level images
We introduce an approach for updating older tree inventories with geographic coordinates
using street-level panorama images and a global optimization framework for tree instance …
using street-level panorama images and a global optimization framework for tree instance …
Simultaneous multi-view instance detection with learned geometric soft-constraints
We propose to jointly learn multi-view geometry and warping between views of the same
object instances for robust cross-view object detection. What makes multi-view object …
object instances for robust cross-view object detection. What makes multi-view object …
Geograph: Graph-based multi-view object detection with geometric cues end-to-end
In this paper we propose an end-to-end learnable approach that detects static urban objects
from multiple views, re-identifies instances, and finally assigns a geographic position per …
from multiple views, re-identifies instances, and finally assigns a geographic position per …
Deep-learning and depth-map based approach for detection and 3-D localization of small traffic signs
L Liu, X Tang, J Xie, X Gao, W Zhao… - IEEE Journal of …, 2020 - ieeexplore.ieee.org
The three-dimensional (3-D) geographic locations of street furniture, such as traffic signs,
comprise the basic content of 3-D city construction, and such information is indispensable for …
comprise the basic content of 3-D city construction, and such information is indispensable for …
[HTML][HTML] Object tracking and geo-localization from street images
Object geo-localization from images is crucial to many applications such as land surveying,
self-driving, and asset management. Current visual object geo-localization algorithms suffer …
self-driving, and asset management. Current visual object geo-localization algorithms suffer …
End-to-end learning improves static object geo-localization from video
Accurately estimating the position of static objects, such as traffic lights, from the moving
camera of a self-driving car is a challenging problem. In this work, we present a system that …
camera of a self-driving car is a challenging problem. In this work, we present a system that …
Object geolocation from crowdsourced street level imagery
We explore the applicability and limitations of a state-of-the-art object detection and
geotagging system [4] applied to crowdsourced image data. Our experiments with imagery …
geotagging system [4] applied to crowdsourced image data. Our experiments with imagery …
End-to-end learning improves static object geo-localization in monocular video
Accurately estimating the position of static objects, such as traffic lights, from the moving
camera of a self-driving car is a challenging problem. In this work, we present a system that …
camera of a self-driving car is a challenging problem. In this work, we present a system that …
[HTML][HTML] Multi-view instance matching with learned geometric soft-constraints
We present a new approach for matching urban object instances across multiple ground-
level images for the ultimate goal of city-scale mapping of objects with high positioning …
level images for the ultimate goal of city-scale mapping of objects with high positioning …
Géolocalisation des objets détectés par une caméra monoculaire à bord d'un véhicule
A Termoul - 2023 - espace.etsmtl.ca
Ce travail se fait dans le cadre d'un projet de recherche financé par le Ministère des
transports du Québec (MTQ) sur l'acquisition de données pour véhicules autonomes …
transports du Québec (MTQ) sur l'acquisition de données pour véhicules autonomes …