FingerSplat：基于3D高斯泼溅的非接触式指纹三维重建与生成
FingerSplat: Contactless Fingerprint 3D Reconstruction and Generation based on 3D Gaussian Splatting
AI总结：
本文提出FingerSplat框架，首次将3D高斯泼溅用于非接触式指纹识别，在无相机参数和稀疏输入条件下实现指纹三维配准、重建与生成，并提升识别性能。
摘要：
研究人员在非接触式指纹方面开展了许多开创性研究，然而非接触式指纹识别的性能仍落后于接触式方法，主要原因是具有姿态变化的非接触式指纹数据不足，以及缺乏对隐式三维指纹表示的利用。本文提出了一种新颖的非接触式指纹三维配准、重建与生成框架，通过融合3D高斯泼溅技术，旨在为融合三维指纹重建与生成的非接触式指纹识别提供一种新范式。据我们所知，这是首次将3D高斯泼溅应用于指纹识别领域的工作，也是首次在输入图像稀疏且无需相机参数信息的情况下，实现非接触式指纹的有效三维配准与完整重建。在三维指纹配准、重建和生成方面的实验证明，我们的方法能够从二维图像中准确对齐并重建三维指纹，并进一步从三维模型生成高质量的非接触式指纹，从而提升非接触式指纹识别的性能。
英文摘要：
Researchers have conducted many pioneer researches on contactless fingerprints, yet the performance of contactless fingerprint recognition still lags behind contact-based methods primary due to the insufficient contactless fingerprint data with pose variations and lack of the usage of implicit 3D fingerprint representations. In this paper, we introduce a novel contactless fingerprint 3D registration, reconstruction and generation framework by integrating 3D Gaussian Splatting, with the goal of offering a new paradigm for contactless fingerprint recognition that integrates 3D fingerprint reconstruction and generation. To our knowledge, this is the first work to apply 3D Gaussian Splatting to the field of fingerprint recognition, and the first to achieve effective 3D registration and complete reconstruction of contactless fingerprints with sparse input images and without requiring camera parameters information. Experiments on 3D fingerprint registration, reconstruction, and generation prove that our method can accurately align and reconstruct 3D fingerprints from 2D images, and sequentially generates high-quality contactless fingerprints from 3D model, thus increasing the performances for contactless fingerprint recognition.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
