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SpecTrack: Learned Multi-Rotation Tracking via Speckle Imaging

Ziyang Chen, Mustafa Doğa Doğan, Josef Spjut, Kaan Akşit

TL;DR

This work investigates Laser Speckle Imaging (LSI), an emerging optical tracking method that offers promising potential for improving pose estimation accuracy, and proposes a proposed LSI-Based Tracking (SpecTrack), which leverages the captures from a lensless camera and a retro-reflector marker with a coded aperture to achieve multi-axis rotational pose estimation with high precision.

Abstract

Precision pose detection is increasingly demanded in fields such as personal fabrication, Virtual Reality (VR), and robotics due to its critical role in ensuring accurate positioning information. However, conventional vision-based systems used in these systems often struggle with achieving high precision and accuracy, particularly when dealing with complex environments or fast-moving objects. To address these limitations, we investigate Laser Speckle Imaging (LSI), an emerging optical tracking method that offers promising potential for improving pose estimation accuracy. Specifically, our proposed LSI-Based Tracking (SpecTrack) leverages the captures from a lensless camera and a retro-reflector marker with a coded aperture to achieve multi-axis rotational pose estimation with high precision. Our extensive trials using our in-house built testbed have shown that SpecTrack achieves an accuracy of 0.31° (std=0.43°), significantly outperforming state-of-the-art approaches and improving accuracy up to 200%.

SpecTrack: Learned Multi-Rotation Tracking via Speckle Imaging

TL;DR

This work investigates Laser Speckle Imaging (LSI), an emerging optical tracking method that offers promising potential for improving pose estimation accuracy, and proposes a proposed LSI-Based Tracking (SpecTrack), which leverages the captures from a lensless camera and a retro-reflector marker with a coded aperture to achieve multi-axis rotational pose estimation with high precision.

Abstract

Precision pose detection is increasingly demanded in fields such as personal fabrication, Virtual Reality (VR), and robotics due to its critical role in ensuring accurate positioning information. However, conventional vision-based systems used in these systems often struggle with achieving high precision and accuracy, particularly when dealing with complex environments or fast-moving objects. To address these limitations, we investigate Laser Speckle Imaging (LSI), an emerging optical tracking method that offers promising potential for improving pose estimation accuracy. Specifically, our proposed LSI-Based Tracking (SpecTrack) leverages the captures from a lensless camera and a retro-reflector marker with a coded aperture to achieve multi-axis rotational pose estimation with high precision. Our extensive trials using our in-house built testbed have shown that SpecTrack achieves an accuracy of 0.31° (std=0.43°), significantly outperforming state-of-the-art approaches and improving accuracy up to 200%.
Paper Structure (2 sections, 4 figures, 1 table)

This paper contains 2 sections, 4 figures, 1 table.

Table of Contents

  1. Introduction
  2. Method

Figures (4)

  • Figure 1: (left) The y-axis rotation demonstration. (right) Top: Photographs showing the speckle patterns when the target object is rotated around the y-axis at different angles. Bottom: The autocorrelation (AC) results of the photographs in the top row (enlarged for visualization).
  • Figure 2: Schematics of the light paths (top). Demonstration of the overlapping speckles (bottom).
  • Figure 3: .
  • Figure 4: Testbed side view (left). Testbed top view (right).