Paper
19 October 2023 Single pig pose estimation using cross-stage stacked hourglass network
Minjuan Wang, Wanwan Li, Wenxin Zhang, Guixin Li, Kun Dong, Lihua Zheng, Yifan He, Yifei Chen
Author Affiliations +
Proceedings Volume 12709, Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023); 127090F (2023) https://doi.org/10.1117/12.2685014
Event: Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023), 2023, Nanjing, China
Abstract
Posture changes in pig behaviors are a helpful way of detecting early signs of precision livestock farming. In commercial settings, computer vision-based approaches have been widely used to obtain individual pig health and welfare information such as body condition score, live weight, and activity behaviors. For this, precisely estimating pig posture is a prerequisite, which is an important step in obtaining real-time pig information. In this paper, a cross-stage stacked hourglass network is conducted to solve pig posture estimation in a real feedlot environment. In addition, a cross-stage connection method that increases the flow of information to mitigate possible information loss is proposed, which obtains 2.1% improvement of PCKh than that of the original network. We trained and tested the proposed approach on a challenging pig dataset, which includes not only real pig images but also images from different websites. The results indicate that it is possible to recognize pig posture from images without any manual interference automatically, and it has great potential for application in the early detection of health and welfare challenges of commercial pigs.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Minjuan Wang, Wanwan Li, Wenxin Zhang, Guixin Li, Kun Dong, Lihua Zheng, Yifan He, and Yifei Chen "Single pig pose estimation using cross-stage stacked hourglass network", Proc. SPIE 12709, Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023), 127090F (19 October 2023); https://doi.org/10.1117/12.2685014
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KEYWORDS
Pose estimation

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