FHNW Muttenz street-view visual localization dataset released with accuracy evaluation
What happened
Jonas Meyer and other authors released the FHNW Muttenz street-view dataset and used it to systematically evaluate sparse-feature visual localization. The dataset covers a continuous 10 km street network and includes two mobile mapping collections about 1.5 years apart, with ground-truth pose position accuracy of 6-9 mm and orientation error below 0.1°. Evaluations show that under daytime imagery and pre-calibrated camera conditions, median translation error is 1-5 cm and rotation error is 0.03-0.1°. The authors state that, provided the scene representation has accurate georeferencing, visual localization can approach survey-grade GNSS positioning accuracy and can provide full orientation information. The dataset has been made public.
AI 根据报道生成 · 2 days ago更新
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- arXiv cs.ROFHNW Muttenz dataset: assessing the accuracy potential of street-level visual localization
The authors release the FHNW Muttenz dataset, covering a contiguous 10 km street network and two mobile mapping campaigns about 1.5 years apart, with ground-truth poses accurate to 6-9 mm in position and orientation error below 0.1°. Using this dataset, they systematically evaluate sparse-feature visual localization; with daytime imagery and pre-calibrated cameras, median translation error is 1-5 cm and rotation error is 0.03-0.1°. The authors note that, provided the scene representation is precisely georeferenced, visual localization can approach survey-grade GNSS positioning accuracy and additionally provides full orientation information.
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