基于图形和多阶段的限制,用于手持物体重建
Wenrun Wang1,2, Jianwu Dang1, Yangping Wang1
1College of Electronics and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China.
Sensors (Basel, Switzerland)
|January 28, 2026
概括
这项研究引入了一种新的方法,用于在交互过程中重建手和物体形状,提高物理精度和几何细节. 该框架使用协作优化来更好地建模手对象交互,并在基准数据集上取得最先进的结果.
科学领域:
- 计算机视觉 计算机视觉
- 机器人技术 机器人技术 机器人技术
- 三维重建的3D重建
背景情况:
- 从单个视图中重建手物互动是很困难的,因为遮蔽和物理可信性要求.
- 现有的方法通常会单独处理手和物体,或者使用后期的后期处理来限制.
研究的目的:
- 开发一个全方位的手对象交互重建的新框架.
- 在整个重建管道中逐步强制执行物理一致性和几何准确性.
主要方法:
- 输入:RGB-D图像. 在输入:RGB-D图像.
- 适应性功能融合,实现强大的颜色和深度集成.
- 结构先验和纹理线索用于精致的3D姿势初始化.
- 密集的相互关注,用于稀疏到密集的网格恢复和相互作用依赖性捕获.
- 接触面的签名距离函数 (SDF) 表示,以确保不穿透.
主要成果:
- 对ObMan和DexYCB基准指标的显著改进,表现优于最先进的技术.
- 奥巴曼数据集:手CDh 0.077厘米2,物体CDo 0.483厘米2.
- 德克斯YCB数据集:手CDh 0.251厘米2,物体CDo 1.127厘米2.
结论:
- 拟议的整体,多阶段的协作优化框架有效地重建了手对象交互.
- 该方法实现了高物理可信性和几何精度,超越了现有技术.
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