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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2401.17714 |
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| _version_ | 1866911768347934720 |
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| author | Mori, Daisuke Hayami, Hiroki Fujimoto, Yasufumi Goto, Isao |
| author_facet | Mori, Daisuke Hayami, Hiroki Fujimoto, Yasufumi Goto, Isao |
| contents | In ecological research, accurately collecting spatiotemporal position data is a fundamental task for understanding the behavior and ecology of insects and other organisms. In recent years, advancements in computer vision techniques have reached a stage of maturity where they can support, and in some cases, replace manual observation. In this study, a simple and inexpensive method for monitoring insects in three dimensions (3D) was developed so that their behavior could be observed automatically in experimental environments. The main achievements of this study have been to create a 3D monitoring algorithm using inexpensive cameras and other equipment to design an adjusting algorithm for depth error, and to validate how our plotting algorithm is quantitatively precise, all of which had not been realized in conventional studies. By offering detailed 3D visualizations of insects, the plotting algorithm aids researchers in more effectively comprehending how insects interact within their environments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_17714 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | 3D-Plotting Algorithm for Insects using YOLOv5 Mori, Daisuke Hayami, Hiroki Fujimoto, Yasufumi Goto, Isao Computer Vision and Pattern Recognition In ecological research, accurately collecting spatiotemporal position data is a fundamental task for understanding the behavior and ecology of insects and other organisms. In recent years, advancements in computer vision techniques have reached a stage of maturity where they can support, and in some cases, replace manual observation. In this study, a simple and inexpensive method for monitoring insects in three dimensions (3D) was developed so that their behavior could be observed automatically in experimental environments. The main achievements of this study have been to create a 3D monitoring algorithm using inexpensive cameras and other equipment to design an adjusting algorithm for depth error, and to validate how our plotting algorithm is quantitatively precise, all of which had not been realized in conventional studies. By offering detailed 3D visualizations of insects, the plotting algorithm aids researchers in more effectively comprehending how insects interact within their environments. |
| title | 3D-Plotting Algorithm for Insects using YOLOv5 |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2401.17714 |