A New Sense for Depth of Field
IEEE Transactions on Pattern Analysis and Machine Intelligence
Single Lens Stereo with a Plenoptic Camera
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Modeling and calibration of automated zoom lenses
Modeling and calibration of automated zoom lenses
Depth from defocus: a spatial domain approach
International Journal of Computer Vision
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
IEEE Transactions on Pattern Analysis and Machine Intelligence
Moment and Hypergeometric Filters for High Precision Computation ofFocus, Stereo and Optical Flow
International Journal of Computer Vision
Recovering high dynamic range radiance maps from photographs
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Telecentric Optics for Focus Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Rational Filters for Passive Depth from Defocus
International Journal of Computer Vision
An MRF Model-Based Approach to Simultaneous Recovery of Depth and Restoration from Defocused Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Dynamically reparameterized light fields
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Depth from Defocus vs. Stereo: How Different Really Are They?
International Journal of Computer Vision - Special issue on computer vision research at the Technion
A Theory of Shape by Space Carving
International Journal of Computer Vision - Special issue on Genomic Signal Processing
Radiometric CCD camera calibration and noise estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Observing Shape from Defocused Images
International Journal of Computer Vision
A Variational Approach to Shape from Defocus
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
Lucas-Kanade 20 Years On: A Unifying Framework
International Journal of Computer Vision
High-quality video view interpolation using a layered representation
ACM SIGGRAPH 2004 Papers
Capture of hair geometry from multiple images
ACM SIGGRAPH 2004 Papers
Synthetic aperture confocal imaging
ACM SIGGRAPH 2004 Papers
Modeling the Space of Camera Response Functions
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Geometric Approach to Shape from Defocus
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image-Based Rendering Using Image-Based Priors
International Journal of Computer Vision
Example-Based Photometric Stereo: Shape Reconstruction with General, Varying BRDFs
IEEE Transactions on Pattern Analysis and Machine Intelligence
ACM SIGGRAPH 2005 Papers
ACM SIGGRAPH 2005 Papers
Modeling hair from multiple views
ACM SIGGRAPH 2005 Papers
Projection defocus analysis for scene capture and image display
ACM SIGGRAPH 2006 Papers
Reconstructing Occluded Surfaces Using Synthetic Apertures: Stereo, Focus and Robust Measures
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Active refocusing of images and videos
ACM SIGGRAPH 2007 papers
ACM SIGGRAPH 2007 papers
Image and depth from a conventional camera with a coded aperture
ACM SIGGRAPH 2007 papers
3D shape from anisotropic diffusion
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Discontinuity-Adaptive Shape from Focus Using a Non-convex Prior
Proceedings of the 31st DAGM Symposium on Pattern Recognition
Real Aperture Axial Stereo: Solving for Correspondences in Blur
Proceedings of the 31st DAGM Symposium on Pattern Recognition
Capturing hair assemblies fiber by fiber
ACM SIGGRAPH Asia 2009 papers
Depth from Encoded Sliding Projections
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part I
Shape from focus using fast discrete curvelet transform
Pattern Recognition
Accurate Depth Dependent Lens Distortion Models: An Application to Planar View Scenarios
Journal of Mathematical Imaging and Vision
Coded Aperture Pairs for Depth from Defocus and Defocus Deblurring
International Journal of Computer Vision
Computational plenoptic imaging
ACM SIGGRAPH 2012 Courses
Two-frame stereo photography in low-light settings: a preliminary study
Proceedings of the 9th European Conference on Visual Media Production
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We present confocal stereo, a new method for computing 3D shape by controlling the focus and aperture of a lens. The method is specifically designed for reconstructing scenes with high geometric complexity or fine-scale texture. To achieve this, we introduce the confocal constancy property, which states that as the lens aperture varies, the pixel intensity of a visible in-focus scene point will vary in a scene-independent way, that can be predicted by prior radiometric lens calibration. The only requirement is that incoming radiance within the cone subtended by the largest aperture is nearly constant. First, we develop a detailed lens model that factors out the distortions in high resolution SLR cameras (12MP or more) with large-aperture lenses (e.g., f1.2). This allows us to assemble an A脳F aperture-focus image (AFI) for each pixel, that collects the undistorted measurements over all A apertures and F focus settings. In the AFI representation, confocal constancy reduces to color comparisons within regions of the AFI, and leads to focus metrics that can be evaluated separately for each pixel. We propose two such metrics and present initial reconstruction results for complex scenes, as well as for a scene with known ground-truth shape.