Depth From Defocus in the Wild
We consider the problem of two-frame depth from defocus in conditions unsuitable for existing methods yet typical of everyday photography: a handheld cellphone camera, a small aperture, a non-stationary scene and sparse surface texture. Our approach combines a global analysis of image content---3D surfaces, deformations, figure-ground relations, textures---with local estimation of joint depth-flow likelihoods in tiny patches. To enable local estimation we (1) derive novel defocus-equalization filters that induce brightness constancy across frames and (2) impose a tight upper bound on defocus blur---just three pixels in radius---through an appropriate choice of the second frame. For global analysis we use a novel piecewise-spline scene representation that can propagate depth and flow across large irregularly-shaped regions. Our experiments show that this combination preserves sharp boundaries and yields good depth and flow maps in the face of significant noise, uncertainty, non-rigidity, and data sparsity.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Deep Depth from Defocus: how can defocus blur improve 3D estimation using dense neural networks?
Depth estimation is of critical interest for scene understanding and accurate 3D reconstruction. Most recent approaches in depth estimation with deep learning exploit geometrical structures of standard sharp images to pr…
3D ReconstructionDepth EstimationDepth PredictionScene UnderstandingMulti-task Learning for Monocular Depth and Defocus Estimations with Real Images
Monocular depth estimation and defocus estimation are two fundamental tasks in computer vision. Most existing methods treat depth estimation and defocus estimation as two separate tasks, ignoring the strong connection be…
Defocus EstimationDepth EstimationMonocular Depth EstimationMulti-Task LearningDepth and DOF Cues Make A Better Defocus Blur Detector
Defocus blur detection (DBD) separates in-focus and out-of-focus regions in an image. Previous approaches mistakenly mistook homogeneous areas in focus for defocus blur regions, likely due to not considering the internal…
Defocus Blur DetectionDepth EstimationMonocular Depth EstimationDark Channel-Assisted Depth-from-Defocus from a Single Image
We estimate scene depth from a single defocus-blurred image using the dark channel as a complementary cue, leveraging its ability to capture local statistics and scene structure. Traditional depth-from-defocus (DFD) meth…
Depth EstimationCamera-Independent Single Image Depth Estimation from Defocus Blur
Monocular depth estimation is an important step in many downstream tasks in machine vision. We address the topic of estimating monocular depth from defocus blur which can yield more accurate results than the semantic bas…
Depth EstimationMonocular Depth Estimation