Generating 3D fish motion skeleton via iterative optimization method and FishSkeletonNet

doi:10.1007/s00371-025-03984-9

	Generating 3D fish motion skeleton via iterative optimization method and FishSkeletonNet
	Shi, Min 1; Zhao, Guo-liang 1; Guo, Shi-sheng 1; Sun, Bi-lian 1; Zhu, Deng-ming 2; Chai, Xiu-juan 3,4; Li, Zhao-xin 3,4; Zhuo, Xin-ru 1
	2025-05-25
发表期刊	VISUAL COMPUTER
ISSN	0178-2789
页码	13
摘要	The fish motion skeleton serves as the foundation for 3D fish motion modeling, enabling the manipulation of fish posture deformations and movements, while also providing a robust framework for analyzing fish behavior to assess their health status and overall performance. However, the joints within the fish motion skeleton, responsible for driving the fish's movements, are not always stable, which undergo changes as the fish grows. The unstable topology of the skeleton poses a challenge when attempting to simulate a lifelike fish skeleton. In this paper, we present a novel method for generating a 3D fish skeleton based on fish posture data. Our approach establishes an initial motion skeleton including the spine and fins. We then determine its parameters, encompassing joint positions and the number of joints, through iterative optimization, employing collected data from fish with various shapes and five common postures as constraints. Furthermore, the skeletons generated through this optimization process are utilized as sample data for training the FishSkeletonNet network, a framework introduced in this paper for predicting fish motion skeletons of input 3D fish bodies. To validate the effectiveness of our approach, we introduce a new dataset of grass carp postures, on which we carry out experiments and conduct both quantitative and qualitative evaluations. The experiments illustrate that our method generates fish motion skeletons that closely emulate the actual motion skeleton structure of fish, demonstrating a higher level of biological plausibility compared to existing methods.
关键词	3D fish body Fish motion skeleton Fish posture Iterative optimization Neural network
DOI	10.1007/s00371-025-03984-9
收录类别	SCI
语种	英语
资助项目	Scientific Instrument Developing Project of the Chinese Academy of Sciences[YJKYYQ20190055] ; National Natural Sciences Foundation of China[62172392] ; Beijing Smart Agriculture innovation Consortium Project[BAlC10-2024] ; Basic Research Center, Innovation Program of Chinese Academy of Agricultural Sciences[CAAS-BRC-SAE-2025-01] ; Basic Research Center, Innovation Program of Chinese Academy of Agricultural Sciences[CAAS-ASTIP-2025-AII] ; Major industrial Research Projects for the Conversion of Old and New Dynamics in Shandong Province[2021-55] ; Innovation Program of Chinese Academy of Agricultural Sciences[CAAS-BRC-SAE-2025-01]
WOS研究方向	Computer Science
WOS类目	Computer Science, Software Engineering
WOS记录号	WOS:001493965000001
出版者	SPRINGER
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/42400
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Li, Zhao-xin
作者单位	1.North China Elect Power Univ, Sch Control & Comp Engn, Beijing 102206, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Prospective Res Lab, Beijing 100190, Peoples R China 3.Chinese Acad Agr Sci, Agr Informat Inst, Beijing 100081, Peoples R China 4.Minist Agr & Rural Affairs, Key Lab Agr Big Data, Beijing 100081, Peoples R China
推荐引用方式 GB/T 7714	Shi, Min,Zhao, Guo-liang,Guo, Shi-sheng,et al. Generating 3D fish motion skeleton via iterative optimization method and FishSkeletonNet[J]. VISUAL COMPUTER,2025:13.
APA	Shi, Min.,Zhao, Guo-liang.,Guo, Shi-sheng.,Sun, Bi-lian.,Zhu, Deng-ming.,...&Zhuo, Xin-ru.(2025).Generating 3D fish motion skeleton via iterative optimization method and FishSkeletonNet.VISUAL COMPUTER,13.
MLA	Shi, Min,et al."Generating 3D fish motion skeleton via iterative optimization method and FishSkeletonNet".VISUAL COMPUTER (2025):13.