arXiv:2604.26920cs.CV2026-04中稿 · CVPR

用彩色闪光同步多视角拍摄,实现低速相机捕捉高速三维动态场景。

Color-Encoded Illumination for High-Speed Volumetric Scene Reconstruction

论文配图:Color-Encoded Illumination for High-Speed Volumetric Scene Reconstruction
图 1 · 摘自论文原文
  • 通过快速切换彩色光照编码时间信息,实现多视角同步高速采集。
  • 首次在真实场景中完成基于普通摄像头的高速三维重建,帧率突破60帧。
  • 无需硬件改造,适合需要低成本高精度动态三维建模的研究者。

近年来,从二维图像中捕捉和渲染三维动态场景的任务日益流行。然而,大多数传统相机受限于30-60帧/秒的带宽,难以处理快速变化的场景。尽管已有多种计算成像方法利用普通相机实现高速视频,但多数需改装光学系统或添加机械部件,仅支持单视角高速采集,无法构建快速运动的三维表示。本文提出一种新方法,仅使用未改装的低速相机即可捕获并重建高速场景的体素化表示。该方法通过快速、顺序的彩色编码光照,将高速动态信息编码进图像的空间强度与颜色变化中,实现多视角同时采集。我们进一步开发了一种基于动态高斯点云的新型重建方法,从图像中解码时间信息。在模拟场景与真实多相机系统实验中验证了该方法,首次实现了基于普通相机的高速三维场景重建。

原文摘要 · Abstract (English)

The task of capturing and rendering 3D dynamic scenes from 2D images has become increasingly popular in recent years. However, most conventional cameras are bandwidth-limited to 30-60 FPS, restricting these methods to static or slowly evolving scenes. While overcoming bandwidth limitations is difficult for general scenes, recent years have seen a flurry of computational imaging methods that yield high-speed videos using conventional cameras for specific applications (e.g., motion capture and particle image velocimetry). However, most of these methods require modifications to a camera's optics or the addition of mechanically moving components, limiting them to a single-view high-speed capture. Consequently, these methods cannot be readily used to capture a 3D representation of rapid scene motion. In this paper, we propose a novel method to capture and reconstruct a volumetric representation of a high-speed scene using only unaugmented low-speed cameras. Instead of modifying the hardware or optics of each individual camera, we encode high-speed scene dynamics by illuminating the scene with a rapid, sequential color-coded sequence. This results in simultaneous multi-view capture of the scene, where high-speed temporal information is encoded in the spatial intensity and color variations of the captured images. To construct a high-speed volumetric representation of the dynamic scene, we develop a novel dynamic Gaussian Splatting-based approach that decodes the temporal information from the images. We evaluate our approach on simulated scenes and real-world experiments using a multi-camera imaging setup, showing first-of-a-kind high-speed volumetric scene reconstructions.

三维重建高速成像计算摄影

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