# Planar Geometry and Image Recovery from Motion-Blur

## TL;DR

This paper introduces a novel method for recovering 3D scene geometry and latent images from a single motion-blurred image of a multi-planar scene, addressing depth-dependent blur effects.

## Contribution

It presents the first approach to estimate scene normals, number of planes, and camera motion from a single motion-blurred image of a 3D scene with arbitrary orientations.

## Key findings

- Achieves state-of-the-art results on synthetic data
- Successfully recovers scene geometry and latent image
- Handles arbitrary plane orientations in 3D scenes

## Abstract

Existing works on motion deblurring either ignore the effects of depth-dependent blur or work with the assumption of a multi-layered scene wherein each layer is modeled in the form of fronto-parallel plane. In this work, we consider the case of 3D scenes with piecewise planar structure i.e., a scene that can be modeled as a combination of multiple planes with arbitrary orientations. We first propose an approach for estimation of normal of a planar scene from a single motion blurred observation. We then develop an algorithm for automatic recovery of number of planes, the parameters corresponding to each plane, and camera motion from a single motion blurred image of a multiplanar 3D scene. Finally, we propose a first-of-its-kind approach to recover the planar geometry and latent image of the scene by adopting an alternating minimization framework built on our findings. Experiments on synthetic and real data reveal that our proposed method achieves state-of-the-art results.