SpecTrack dataset

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%.

在个性化制造、虚拟现实（VR）和机器人技术等领域，精确姿态检测的需求日益增长，这在确保精确定位信息方面发挥着至关重要的作用。然而，这些系统中常用的基于传统视觉的系统往往难以实现高精度和准确度，尤其是在处理复杂环境或快速移动的物体时。为了解决这些局限性，我们研究了激光散斑成像（LSI），这是一种新兴的光学跟踪方法，它为提高姿态估计精度提供了有希望的潜力。具体而言，我们提出的基于LSI的跟踪（SpecTrack）技术利用无镜头相机和带有编码孔径的反向反射器标记的捕获数据，以实现多轴旋转姿态的高精度估计。通过我们自行构建的测试平台进行的广泛试验表明，SpecTrack实现了0.31°（标准差=0.43°）的精度，显著优于现有技术，并提高了精度至200%。