神话姿势:增强探测卡形象中的复杂姿势
Yukai Xian1, Te Shen1, Yurui Lee2
1School of Information Science and Technology, Tibet University, Lhasa 850000, China.
Sensors (Basel, Switzerland)
|August 28, 2025
概括
这项研究介绍了MythPose, 一种用于精确检测藏族Thangka艺术中人类姿势的AI模型, 它提升了对这一独特文化遗产的数字保护和理解.
科学领域:
- 计算机视觉
- 人工智能
- 数字艺术保存
背景情况:
- 西藏的卡绘画具有丰富的文化和艺术价值,
- 传统的人体姿势估计方法与卡艺术的独特特征作斗争.
- 精确的关键点检测对于数字保存和分析卡绘画至关重要.
研究的目的:
- 开发一个先进的人体姿势估计模型,
- 在非标准的人形艺术品中提高关键点检测的准确性和稳定性.
- 通过更好的姿势估计, 促进数字保存和学术分析.
主要方法:
- 在YOLOv11-Pose架构的基础上,整合了Mamba结构以增强全球特征捕获.
- 实施特征融合模块以有效地整合浅层和深层视觉特征.
- 提出一种新的KAL损失函数来减轻不同身体部位的关键点之间的干扰.
- 创建和注释6208张Thangka图像的专用数据集,
主要成果:
- 提出的MythPose模型取得了显著的性能,在Thangka图像上达到89.13%的mAP@0.5,92.51%的PCK和87.22%的OKS.
- 与基线模型相比,MythPose在Thangka数据集上的人类姿势估计任务中表现出更好的表现.
- 这个模型有效地处理了标准和多个肢体的图像,
结论:
- 在西藏的卡绘画中, MythPose 提供了一个强大的解决方案,
- 这项研究为数字保存和研究卡艺术提供了宝贵的工具.
- 开发的技术在其他复杂的风格艺术作品中提供了对姿势估计的潜在应用.
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