Color-Encoded Illumination for High-Speed Volumetric Scene Reconstruction
2026-04-29 • Computer Vision and Pattern Recognition
Computer Vision and Pattern Recognition
AI summaryⓘ
The authors developed a new way to capture fast-moving 3D scenes using regular slow cameras without changing their hardware. They shine quickly changing colored lights on the scene to hide fast motion information in the colors and brightness captured by multiple cameras. Then, they use a special method called dynamic Gaussian Splatting to decode these colors and create detailed 3D videos of fast actions. Their tests include both computer simulations and real experiments, showing this approach can capture fast 3D movements with normal cameras.
3D dynamic sceneshigh-speed videocomputational imagingmulti-view capturecolor-coded illuminationGaussian Splattingvolumetric reconstructiontemporal encodingparticle image velocimetrymotion capture
Authors
David Novikov, Eilon Vaknin, Narek Tumanyan, Mark Sheinin
Abstract
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.