Description
This dataset is an extension of The Growing Strawberries Dataset (GSD), a curated multiple-object tracking (MOT) dataset originally developed for monitoring strawberry growth. It comprises hourly images captured during the cultivation periods of 2023 and 2024, featuring 10–13 plants in two distinct greenhouses.
The 2023 data includes two types of images—RGB (visual spectrum) and OCN (orange, cyan, near-infrared)—captured by three pairs of cameras, consistent with the setup of the original GSD (doi.org/10.4121/e3b31ece-cc88-4638-be10-8ccdd4c5f2f7). In 2024, the setup was adjusted to four RGB cameras and two overhead cameras, enabling more comprehensive multi-perspective monitoring.
The 2023 data includes two types of images—RGB (visual spectrum) and OCN (orange, cyan, near-infrared)—captured by three pairs of cameras, consistent with the setup of the original GSD (doi.org/10.4121/e3b31ece-cc88-4638-be10-8ccdd4c5f2f7). In 2024, the setup was adjusted to four RGB cameras and two overhead cameras, enabling more comprehensive multi-perspective monitoring.
| Date made available | 14 Jan 2025 |
|---|---|
| Publisher | TU Delft - 4TU.ResearchData |
| Geographical coverage | Kronenberg (2023) and Bleiswijk (2024), The Netherlands |
Research output
- 1 Conference contribution
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The Growing Strawberries Dataset: Tracking Multiple Objects with Biological Development over an Extended Period
Wen, J., Verschoor, C. R., Feng, C., Epure, I. M., Abeel, T. & De Weerdt, M., 2024, Proceedings - 2024 IEEE Winter Conference on Applications of Computer Vision, WACV 2024. IEEE, p. 7089-7099 11 p. (Proceedings - 2024 IEEE Winter Conference on Applications of Computer Vision, WACV 2024).Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review
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