High-Throughput Plant Height Estimation from RGB Images Acquired with Aerial Platforms: A 3D Point Cloud Based Approach

Abstract

With the development of computer vision technologies, using images acquired by aerial platforms to measure large scale agricultural fields has been increasingly studied. In order to provide a more time efficient, light weight and low cost solution, in this paper we present a highly automated processing pipeline that performs plant height estimation based on a dense point cloud generated from aerial RGB images, requiring only a single flight. A previously acquired terrain model is not required as input. The process extracts a segmented plant layer and bare ground layer. Ground height estimation achieves sub 10cm accuracy. High throughput plant height estimation has been performed and results are compared with LiDAR based measurements.