3D Motion Estimation Using Defocused Speckle Images
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Solution Overview
Problem
Current speckle imaging techniques are limited to measuring 2D motion of a single rigid object and are not suitable for estimating small motions in three dimensions, particularly axial motion, or multi-object motion, due to their limited sensitivity and complexity.
Innovation Solution
A system and method using temporally coherent light and an image sensor to capture defocused speckle patterns, analyzing these patterns by generating scaled versions and calculating cross-correlations to determine both axial and lateral motion of objects in three dimensions, enabling the estimation of micro-motions at macroscopic stand-off distances and multi-object motion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional speckle imaging techniques are used, then 2D motion of a single rigid object can be measured, but 3D motion estimation including axial motion remains difficult
Solution Approach 1:
The patent transitions from 2D speckle pattern analysis to 3D motion estimation by introducing axial motion measurement capabilities. This is achieved through defocused imaging that captures speckle patterns with depth information, enabling measurement of motion components along the optical axis in addition to lateral motion components.
Solution Approach 2:
The system is designed to measure multiple types of motion (axial and lateral) simultaneously using a unified speckle imaging approach. The defocused imaging technique provides a versatile framework that can estimate both axial and lateral motion components from the same captured speckle patterns, making the system adaptable to various motion analysis requirements.
2Measurement precision
If sophisticated optics are used to measure micro-motions at macroscopic stand-off distances, then measurement capability is improved, but device complexity increases
Solution Approach 1:
The system uses naturally formed speckle patterns created by coherent light reflecting off rough surfaces at macroscopic distances. These speckle patterns inherently contain motion information that can be extracted through image processing, eliminating the need for complex specialized optics designed specifically for micro-motion detection.
Solution Approach 2:
The patent replaces complex mechanical/optical measurement systems with a computational approach. By capturing defocused speckle images and analyzing them through cross-correlation and scaling techniques, the system achieves micro-motion detection capabilities without requiring sophisticated optical components.
3Device complexity
If conventional imaging is used for multi-object or non-rigid motion measurement, then system simplicity is maintained, but measurement capability fundamentally deteriorates due to higher degrees of freedom
Solution Approach 1:
The patent separates the motion analysis into distinct components by processing different scaled versions of speckle images. By generating and comparing multiple scaled versions of the first defocused image with the second defocused image, the system can isolate and measure axial and lateral motion components independently, even in multi-object or non-rigid scenarios.
4Adaptability or versatility
If axial motion measurement is added to speckle imaging, then 3D motion estimation capability is improved, but processing complexity increases due to scaling operations
Solution Approach 1:
The system performs preliminary scaling operations on the first defocused image to create multiple scaled versions before comparison. This preliminary preparation enables the subsequent cross-correlation process to efficiently extract axial motion information by comparing how different scaled versions match the second defocused image, separating axial from lateral motion components.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for precise measurement of small axial and lateral motions in three dimensions, enhancing the sensitivity of motion estimation and enabling applications such as hand gesture recognition and motion analysis in complex scenes.
Implementation Method 1
a first defocused image of the scene at a first time, wherein the first defocused image includes a first speckle pattern generated by an object in the scene reflecting the light emitted by the light source
Data Source
AI summary
In accordance with some embodiments, systems, methods and media for determining object motion in three dimensions using speckle images are provided. In some embodiments, a system for three dimensional motion estimation is provided, comprising: a light source; an image sensor; and a hardware processor programmed to: cause the light source to emit light toward the scene; cause the image sensor to capture a first defocused speckle image of the scene at a first time and capture a second defocused speckle image of the scene at a second time; generate a first scaled version of the first defocused image; generate a second scaled version of the first defocused image; compare each of the first defocused image, the first scaled version, and the second scaled version to the second defocused image; and determine axial and lateral motion of the object based on the comparisons.