A New Sense for Depth of Field
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Investigation of Methods for Determining Depth from Focus
IEEE Transactions on Pattern Analysis and Machine Intelligence
Active vision for reliable ranging: cooperating focus, stereo, and vergence
International Journal of Computer Vision
Markov random field modeling in computer vision
Markov random field modeling in computer vision
Recovering Affine Motion and Defocus Blur Simultaneously
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Telecentric Optics for Computational Vision
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Depth Estimation and Image Restoration Using Defocused Stereo Pairs
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Geometric Approach to Shape from Defocus
IEEE Transactions on Pattern Analysis and Machine Intelligence
Geo-Consistency for Wide Multi-Camera Stereo
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Error Analysis for Image Inpainting
Journal of Mathematical Imaging and Vision
Shape from Defocus via Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Range Map with Missing Data - Joint Resolution Enhancement and Inpainting
ICVGIP '08 Proceedings of the 2008 Sixth Indian Conference on Computer Vision, Graphics & Image Processing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real Aperture Axial Stereo: Solving for Correspondences in Blur
Proceedings of the 31st DAGM Symposium on Pattern Recognition
Removing image artifacts due to dirty camera lenses and thin occluders
ACM SIGGRAPH Asia 2009 papers
Shape from Sharp and Motion-Blurred Image Pair
International Journal of Computer Vision
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Traditional depth estimation methods typically exploit the effect of either the variations in internal parameters such as aperture and focus (as in depth from defocus), or variations in extrinsic parameters such as position and orientation of the camera (as in stereo). When operating off-the-shelf (OTS) cameras in a general setting, these parameters influence the depth of field (DOF) and field of view (FOV). While DOF mandates one to deal with defocus blur, a larger FOV necessitates camera motion during image acquisition. As a result, for unfettered operation of an OTS camera, it becomes inevitable to account for pixel motion as well as optical defocus blur in the captured images. We propose a depth estimation framework using calibrated images captured under general camera motion and lens parameter variations. Our formulation seeks to generalize the constrained areas of stereo and shape from defocus (SFD)/focus (SFF) by handling, in tandem, various effects such as focus variation, zoom, parallax and stereo occlusions, all under one roof. One of the associated challenges in such an unrestrained scenario is the problem of removing user-defined foreground occluders in the reference depth map and image (termed inpainting of depth and image). Inpainting is achieved by exploiting the cue from motion parallax to discover (in other images) the correspondence/color information missing in the reference image. Moreover, considering the fact that the observations could be differently blurred, it is important to ensure that the degree of defocus in the missing regions (in the reference image) is coherent with the local neighbours (defocus inpainting).