Dense Pixel-wise Micro-motion Estimation of Object Surface by using Low Dimensional Embedding of Laser Speckle Pattern

TL;DR

This paper introduces a novel laser speckle-based method for pixel-wise micro-motion estimation of object surfaces, utilizing low-dimensional embedding to detect subtle out-of-plane movements.

Contribution

It presents a new active-lighting approach combined with nonlinear embedding of speckle patterns to accurately estimate micro- and large-scale surface motions at each pixel.

Findings

Effective micro-motion detection demonstrated through experiments

Outperforms traditional measurement devices in accuracy

Successfully estimates out-of-plane surface motion

Abstract

This paper proposes a method of estimating micro-motion of an object at each pixel that is too small to detect under a common setup of camera and illumination. The method introduces an active-lighting approach to make the motion visually detectable. The approach is based on speckle pattern, which is produced by the mutual interference of laser light on object's surface and continuously changes its appearance according to the out-of-plane motion of the surface. In addition, speckle pattern becomes uncorrelated with large motion. To compensate such micro- and large motion, the method estimates the motion parameters up to scale at each pixel by nonlinear embedding of the speckle pattern into low-dimensional space. The out-of-plane motion is calculated by making the motion parameters spatially consistent across the image. In the experiments, the proposed method is compared with other measuring devices to prove the effectiveness of the method.