Automated Visual Monitoring of Nocturnal Insects with Light-based Camera
  Traps
Dimitri Korsch Paul Bodesheim Gunnar Brehm Joachim Denzler
Automatic camera-assisted monitoring of insects for abundance estimations is
crucial to understand and counteract ongoing insect decline. In this paper, we
present two datasets of nocturnal insects, especially moths as a subset of
Lepidoptera, photographed in Central Europe. One of the datasets, the EU-Moths
dataset, was captured manually by citizen scientists and contains species
annotations for 200 different species and bounding box annotations for those.
We used this dataset to develop and evaluate a two-stage pipeline for insect
detection and moth species classification in previous work. We further
introduce a prototype for an automated visual monitoring system. This prototype
produced the second dataset consisting of more than 27,000 images captured on
95 nights. For evaluation and bootstrapping purposes, we annotated a subset of
the images with bounding boxes enframing nocturnal insects. Finally, we present
first detection and classification baselines for these datasets and encourage
other scientists to use this publicly available data.