Publikation
Towards Auto-Generated Ground Truth for Evaluation of Perception Systems in Agriculture
Jan Christoph Krause; Mark Niemeyer; Janosch Bajorath; Naeem Iqbal; Joachim Hertzberg
In: Alessio Del Bue; Cristian Canton; Jordi Pont-Tuset; Tatiana Tommasi (Hrsg.). Computer Vision - ECCV 2024 Workshops. Computer Vision in Plant Phenotyping and Agriculture (CVPPA-2024), 9th Computer Vision in Plant Phenotyping and Agriculture, located at 18th European Conference on Computer Vision ECCV 2024, September 29 - October 4, Milano, Italy, Pages 194-206, Lecture Notes in Computer Science (LNCS), Vol. 15625, ISBN 978-3-031-91835-3, Springer, Cham, 5/2025.
Zusammenfassung
Reliable perception of surrounding environment of an agricultural machine is essential for safe and thorough operation. For the development and evaluation of perception systems, a huge amount of comparable data from any operating conditions is mandatory. Since labelling sensor data involves a significant amount of manual work, a reduction in this effort is desirable. Therefore, a setup for surveying static objects during field tests is proposed. Based on RTK measurements, object positions are projected into sensor frames to generate ground truth bounding boxes and centre points for evaluation of perception algorithms. This approach enables automated labelling of images and point clouds generated by cameras, depth cameras, radar and LiDAR systems.