An object's interior material properties, while invisible to the human eye, determine motion observed on its surface. We propose an approach that estimates heterogeneous material properties of an object directly from a monocular video of its surface vibrations. Specifically, we estimate Young's modulus and density throughout a 3D object with known geometry. Knowledge of how these values change across the object is useful for characterizing defects and simulating how the object will interact with different environments. Traditional non-destructive testing approaches, which generally estimate homogenized material properties or the presence of defects, are expensive and use specialized instruments. We propose an approach that leverages monocular video to (1) measure and object's sub-pixel motion and decompose this motion into image-space modes, and (2) directly infer spatially-varying Young's modulus and density values from the observed image-space modes. On both simulated and real videos, we demonstrate that our approach is able to image material properties simply by analyzing surface motion. In particular, our method allows us to identify unseen defects on a 2D drum head from real, high-speed video.
翻译:物体的内物质特性,虽然是人类眼睛看不见的,却决定了物体表面的运动。 我们提出一种方法,直接从表面振动的单视视频中估计物体的不同物质特性。 具体地说, 我们估计了3D对象中已知几何特征的微积分和密度。 了解物体的内物质特性是如何变化的, 有助于辨别缺陷, 模拟物体与不同环境的相互作用。 传统的非破坏性试验方法, 通常估计同质物质特性或存在缺陷, 是昂贵的, 并且使用专门仪器。 我们提出一种方法, 利用单视视频(1) 测量和物体的次像素运动, 并将这种运动分解成图像空间模式, (2) 直接从观察到的图像- 空间模式直接吸收空间变化的Young的微积分和密度值。 在模拟和真实的录像中, 我们证明我们的方法能够仅仅通过分析表面运动来模拟物质特性。 特别是, 我们的方法使我们能够从真实的、 高速视频中辨别出2D 鼓头上看不见的缺陷。