# Pro-Cam SSfM: Projector-Camera System for Structure and Spectral Reflectance from Motion

arXiv: https://arxiv.org/abs/1908.08185 · HTML: https://mlsanity.com/paper/1908.08185/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Aug 2019.

## Built on by (most cited first, 9 of 9)

- [Spec-NeRF: Multi-spectral Neural Radiance Fields](https://mlsanity.com/paper/2310.12987/) (2023)
- [Spectral MVIR: Joint Reconstruction of 3D Shape and Spectral Reflectance](https://mlsanity.com/paper/2104.07308/) (2021)
- [GS-ProCams: Gaussian Splatting-based Projector-Camera Systems](https://mlsanity.com/paper/2412.11762/) (2024)
- [Deep Hyperspectral-Depth Reconstruction Using Single Color-Dot Projection](https://mlsanity.com/paper/2204.03929/) (2022)
- [Dispersed Structured Light for Hyperspectral 3D Imaging](https://mlsanity.com/paper/2311.18287/) (2023)
- [Multi-View Neural Surface Reconstruction with Structured Light](https://mlsanity.com/paper/2211.11971/) (2022)
- [Dense Dispersed Structured Light for Hyperspectral 3D Imaging of Dynamic Scenes](https://mlsanity.com/paper/2412.01140/) (2024)
- [Spectral 3D Computer Vision -- A Review](https://mlsanity.com/paper/2302.08054/) (2023)
- [Lumosaic: Hyperspectral Video via Active Illumination and Coded-Exposure Pixels](https://mlsanity.com/paper/2602.22140/) (2026)

## Abstract (arXiv)

In this paper, we propose a novel projector-camera system for practical and low-cost acquisition of a dense object 3D model with the spectral reflectance property. In our system, we use a standard RGB camera and leverage an off-the-shelf projector as active illumination for both the 3D reconstruction and the spectral reflectance estimation. We first reconstruct the 3D points while estimating the poses of the camera and the projector, which are alternately moved around the object, by combining multi-view structured light and structure-from-motion (SfM) techniques. We then exploit the projector for multispectral imaging and estimate the spectral reflectance of each 3D point based on a novel spectral reflectance estimation model considering the geometric relationship between the reconstructed 3D points and the estimated projector positions. Experimental results on several real objects demonstrate that our system can precisely acquire a dense 3D model with the full spectral reflectance property using off-the-shelf devices.