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arXiv · 2110.12331

A methodology for detection and localization of fruits in apples orchards from aerial images

Thiago T. Santos·Luciano Gebler
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Abstract

Computer vision methods based on convolutional neural networks (CNNs) have presented promising results on image-based fruit detection at ground-level for different crops. However, the integration of the detections found in different images, allowing accurate fruit counting and yield prediction, have received less attention. This work presents a methodology for automated fruit counting employing aerial-images. It includes algorithms based on multiple view geometry to perform fruits tracking, not just avoiding double counting but also locating the fruits in the 3-D space. Preliminary assessments show correlations above 0.8 between fruit counting and true yield for apples. The annotated dataset employed on CNN training is publicly available.

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Thiago T. Santos, Luciano Gebler. 2021-10-24. A methodology for detection and localization of fruits in apples orchards from aerial images. https://arxiv.org/abs/2110.12331

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