Authors:
Regina Pohle-Fröhlich
;
Colin Gebler
and
Tobias Bolten
Affiliation:
Institute for Pattern Recognition, Niederrhein University of Applied Sciences, Krefeld, Germany
Keyword(s):
Event Camera, Segmentation, Insect Monitoring, Depth Estimation.
Abstract:
To investigate the causes of declining insect populations, a monitoring system is needed that automatically records insect activity and additional environmental factors over an extended period of time. For this reason, we use a sensor-based method with two event cameras. In this paper, we describe the system, the view volume that can be recorded with it, and a database used for insect detection. We also present the individual steps of our developed processing pipeline for insect monitoring. For the extraction of insect trajectories, a U-Net based segmentation was tested. For this purpose, the events within a time period of 50 ms were transformed into a frame representation using four different encoding types. The tested histogram encoding achieved the best results with an F1 score for insect segmentation of 0.897 and 0.967 for plant movement and noise parts. The detected trajectories were then transformed into a 4D representation, including depth, and visualized.