Distortion Estimation Through Explicit Modeling of the Refractive Surface
Precise calibration is a must for high reliance 3D computer vision algorithms. A challenging case is when the camera is behind a protective glass or transparent object: due to refraction, the image is heavily distorted; the pinhole camera model alone can not be used and a distortion correction step is required. By directly modeling the geometry of the refractive media, we build the image generation process by tracing individual light rays from the camera to a target. Comparing the generated images to their distorted - observed - counterparts, we estimate the geometry parameters of the refractive surface via model inversion by employing an RBF neural network. We present an image collection methodology that produces data suited for finding the distortion parameters and test our algorithm on synthetic and real-world data. We analyze the results of the algorithm.
Code (0)
등록된 구현이 없습니다.
Tasks
distortion correctionImage GenerationSimilar Papers 제목 키워드 기반
Refractive Structure-From-Motion Through a Flat Refractive Interface
Recovering 3D scene geometry from underwater images involves the Refractive Structure-from-Motion (RSfM) problem, where the image distortions caused by light refraction at the interface between different propagation medi…
Camera Pose EstimationPose EstimationA unified Benchmark for Multi-Frame Image Restoration under Severe Refractive Warping
Video sequence capturing through refractive dynamic media, such as a turbulent air or water surface, often suffer from severe geometric distortions and temporal instability. While recent advances address mild atmospheric…
Image RestorationRefracGS: Novel View Synthesis Through Refractive Water Surfaces with 3D Gaussian Ray Tracing
Novel view synthesis (NVS) through non-planar refractive surfaces presents fundamental challenges due to severe, spatially varying optical distortions. While recent representations like NeRF and 3D Gaussian Splatting (3D…
Novel View SynthesisNeRFrac: Neural Radiance Fields through Refractive Surface
Neural Radiance Fields (NeRF) is a popular neural expression for novel view synthesis. By querying spatial points and view directions, a multilayer perceptron (MLP) can be trained to output the volume density and rad…
NeRFNovel View SynthesisSimulating Refractive Distortions and Weather-Induced Artifacts for Resource-Constrained Autonomous Perception
The scarcity of autonomous vehicle datasets from developing regions, particularly across Africa's diverse urban, rural, and unpaved roads, remains a key obstacle to robust perception in low-resource settings. We present …
Image Restoration