SC-OmniGS：自校准全向高斯溅射
SC-OmniGS: Self-Calibrating Omnidirectional Gaussian Splatting
AI总结：
SC-OmniGS提出一种自校准全向高斯溅射方法，通过将360度图像视为球体并引入可微全向相机模型，联合优化相机内参、位姿与三维高斯，实现无需精确位姿先验的高质量全向辐射场重建。
摘要：
360度相机通过捕获全面的场景数据，简化了辐射场三维重建的数据采集过程。然而，传统的辐射场方法并未解决360度图像所固有的特定挑战。我们提出SC-OmniGS，一种新颖的自校准全向高斯溅射系统，用于利用360度图像实现快速且准确的全向辐射场重建。我们没有将360度图像转换为立方体贴图并执行透视图像校准，而是将360度图像视为一个完整的球体，并推导出一个数学框架，使得能够直接进行全向相机位姿校准，同时伴随三维高斯优化。此外，我们引入了一个可微分的全向相机模型，以校正真实世界数据的畸变，从而提升性能。总体而言，全向相机内参模型、外部位姿和三维高斯通过最小化加权球面光度损失进行联合优化。大量实验表明，我们提出的SC-OmniGS能够在以宽基线和非物体中心配置为特征的挑战性场景中，从含噪声的相机位姿甚至完全没有位姿先验的情况下恢复出高质量的辐射场。在由消费级全向相机采集的真实世界数据集上取得的显著性能提升，验证了我们的通用全向相机模型在减少360度图像畸变方面的有效性。
英文摘要：
360-degree cameras streamline data collection for radiance field 3D reconstruction by capturing comprehensive scene data. However, traditional radiance field methods do not address the specific challenges inherent to 360-degree images. We present SC-OmniGS, a novel self-calibrating omnidirectional Gaussian splatting system for fast and accurate omnidirectional radiance field reconstruction using 360-degree images. Rather than converting 360-degree images to cube maps and performing perspective image calibration, we treat 360-degree images as a whole sphere and derive a mathematical framework that enables direct omnidirectional camera pose calibration accompanied by 3D Gaussians optimization. Furthermore, we introduce a differentiable omnidirectional camera model in order to rectify the distortion of real-world data for performance enhancement. Overall, the omnidirectional camera intrinsic model, extrinsic poses, and 3D Gaussians are jointly optimized by minimizing weighted spherical photometric loss. Extensive experiments have demonstrated that our proposed SC-OmniGS is able to recover a high-quality radiance field from noisy camera poses or even no pose prior in challenging scenarios characterized by wide baselines and non-object-centric configurations. The noticeable performance gain in the real-world dataset captured by consumer-grade omnidirectional cameras verifies the effectiveness of our general omnidirectional camera model in reducing the distortion of 360-degree images.
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