3D Computer Vision Algorithms for Semantic Reconstruction of Agricultural Environments [thesis]
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Author

Wenbo Dong (Ph.D. 2020)

Abstract

Vision sensors mounted on mobile robotic platforms hold great promise in automated agriculture management. However, established computer vision techniques often fail to perform well in agricultural environments due to the environmental complexity, which makes automation difficult. To address this problem, we have designed and developed three-dimensional (3D) computer vision algorithms that improve the accuracy of imaging devices, suppress the undesirable environmental interferences, and generate accurate and precise 3D models of plants with detailed information automatically extracted for farmers. This dissertation is roughly separated into three main parts.

Link to full paper

3D Computer Vision Algorithms for Semantic Reconstruction of Agricultural Environments

Keywords

agriculture, computer vision

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