Journal article

BREJCHA Jan and ČADÍK Martin. GeoPose3K: Mountain Landscape Dataset for Camera Pose Estimation in Outdoor Environments. Image and Vision Computing. Washington: Elsevier Science, 2017, vol. 2017, no. 1, pp. 1-41. ISSN 0262-8856.
Publication language:english
Original title:GeoPose3K: Mountain Landscape Dataset for Camera Pose Estimation in Outdoor Environments
Title (cs):GeoPose3K: Dataset horské krajiny pro odhad pozice a orientace kamery v přírodním prostředí
Pages:1-41
Place:US
Year:2017
Journal:Image and Vision Computing, Vol. 2017, No. 1, Washington, US
ISSN:0262-8856
Keywords

camera pose estimation, visual geo-localization,camera orientation estimation,image-to-model registration, digital terrain models, semantic segmentation 

Annotation

We introduce a new dataset called GeoPose3K which contains over three thousand precise camera poses of mountain landscape images. In addition to camera location and orientation, we provide data for training and evaluation of computer vision methods and applications in context of outdoor scenes; synthetic depth maps, normal maps, illumination simulation and semantic labels. To illustrate properties of the dataset, we compare results achieved by state-of-the-art visual geo-localization method on GeoPose3K with results achieved on an existing dataset for visual geo-localization. To foster research of computer vision algorithms for outdoor environments, we propose several novel future use-cases of our new GeoPose3K dataset. 

BibTeX:
@ARTICLE{
   author = {Jan Brejcha and Martin {\v{C}}ad{\'{i}}k},
   title = {GeoPose3K: Mountain Landscape Dataset for Camera Pose
	Estimation in Outdoor Environments},
   pages = {1--41},
   journal = {Image and Vision Computing},
   volume = {2017},
   number = {1},
   year = {2017},
   ISSN = {0262-8856},
   language = {english},
   url = {http://www.fit.vutbr.cz/research/view_pub.php.en.iso-8859-2?id=11463}
}

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