デンマーク航空・地上データセット：空撮と街路画像の場所認識・位置推定
Danish Airs and Grounds: A Dataset for Aerial-to-Street-Level Place Recognition and Localization
空撮画像と街路画像を大量に集め、視点や照明の大きな違いを超えて場所を認識・位置推定するためのデータセットDAGを構築し、空撮からの3D復元と街路画像マッチングによる再位置推定手法も提案した。
著者: Andrea Vallone, Frederik Warburg, Hans Hansen, Søren Hauberg, Javier Civera
分類: cs.CV, cs.RO
原文アブストラクト
Place recognition and visual localization are particularly challenging in wide baseline configurations. In this paper, we contribute with the \emph{Danish Airs and Grounds} (DAG) dataset, a large collection of street-level and aerial images targeting such cases. Its main challenge lies in the extreme viewing-angle difference between query and reference images with consequent changes in illumination and perspective. The dataset is larger and more diverse than current publicly available data, including more than 50 km of road in urban, suburban and rural areas. All images are associated with accurate 6-DoF metadata that allows the benchmarking of visual localization methods. We also propose a map-to-image re-localization pipeline, that first estimates a dense 3D reconstruction from the aerial images and then matches query street-level images to street-level renderings of the 3D model. The dataset can be downloaded at: https://frederikwarburg.github.io/DAG
