Label efficient lifelong multi-view broiler detection
- Author
- Thorsten Cardoen (UGent) , Sam Leroux (UGent) and Pieter Simoens (UGent)
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- Project
- Abstract
- Broiler localization is crucial for welfare monitoring, particularly in identifying issues such as wet litter. We focus on multi-camera detection systems since multiple viewpoints not only ensure comprehensive pen coverage but also reduce occlusions caused by lighting, feeder and drinking equipment. Previous multi-view detection studies localize subjects either by aggregating ground plane projections of single-view predictions or by developing end-to-end multi-view detectors capable of directly generating predictions. However, single-view detections may suffer from reduced accuracy due to occlusions, and obtaining ground plane labels for training end-to-end multi-view detectors is challenging. In this paper, we combine the strengths of both approaches by using the readily available aggregated single-view detections as labels for training a multi-view detector. Our approach alleviates the need for hard-to-acquire ground-plane labels. Through experiments on a real-world broiler dataset, we demonstrate the effectiveness of our approach.
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Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-01J2X51SSYVSMB7B75JJMJ9XDV
- MLA
- Cardoen, Thorsten, et al. “Label Efficient Lifelong Multi-View Broiler Detection.” 2024 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS, CVPRW, IEEE, 2024, pp. 5393–402, doi:10.1109/CVPRW63382.2024.00548.
- APA
- Cardoen, T., Leroux, S., & Simoens, P. (2024). Label efficient lifelong multi-view broiler detection. 2024 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS, CVPRW, 5393–5402. https://doi.org/10.1109/CVPRW63382.2024.00548
- Chicago author-date
- Cardoen, Thorsten, Sam Leroux, and Pieter Simoens. 2024. “Label Efficient Lifelong Multi-View Broiler Detection.” In 2024 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS, CVPRW, 5393–5402. IEEE. https://doi.org/10.1109/CVPRW63382.2024.00548.
- Chicago author-date (all authors)
- Cardoen, Thorsten, Sam Leroux, and Pieter Simoens. 2024. “Label Efficient Lifelong Multi-View Broiler Detection.” In 2024 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS, CVPRW, 5393–5402. IEEE. doi:10.1109/CVPRW63382.2024.00548.
- Vancouver
- 1.Cardoen T, Leroux S, Simoens P. Label efficient lifelong multi-view broiler detection. In: 2024 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS, CVPRW. IEEE; 2024. p. 5393–402.
- IEEE
- [1]T. Cardoen, S. Leroux, and P. Simoens, “Label efficient lifelong multi-view broiler detection,” in 2024 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS, CVPRW, Seattle, WA, USA, 2024, pp. 5393–5402.
@inproceedings{01J2X51SSYVSMB7B75JJMJ9XDV,
abstract = {{Broiler localization is crucial for welfare monitoring, particularly in identifying issues such as wet litter. We focus on multi-camera detection systems since multiple viewpoints not only ensure comprehensive pen coverage but also reduce occlusions caused by lighting, feeder and drinking equipment. Previous multi-view detection studies localize subjects either by aggregating ground plane projections of single-view predictions or by developing end-to-end multi-view detectors capable of directly generating predictions. However, single-view detections may suffer from reduced accuracy due to occlusions, and obtaining ground plane labels for training end-to-end multi-view detectors is challenging. In this paper, we combine the strengths of both approaches by using the readily available aggregated single-view detections as labels for training a multi-view detector. Our approach alleviates the need for hard-to-acquire ground-plane labels. Through experiments on a real-world broiler dataset, we demonstrate the effectiveness of our approach.}},
author = {{Cardoen, Thorsten and Leroux, Sam and Simoens, Pieter}},
booktitle = {{2024 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS, CVPRW}},
isbn = {{9798350365481}},
issn = {{2160-7508}},
language = {{eng}},
location = {{Seattle, WA, USA}},
pages = {{5393--5402}},
publisher = {{IEEE}},
title = {{Label efficient lifelong multi-view broiler detection}},
url = {{http://doi.org/10.1109/CVPRW63382.2024.00548}},
year = {{2024}},
}
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