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Proceedings ArticleDOI

Inferring Plane Orientation from a Single Motion Blurred Image

TLDR
The proposed method can accurately infer the normal of the planar surface by leveraging the homography relationship among image coordinates of 3D points lying on a plane and exploiting natural correspondences among the extremities of the blur kernels derived from the motion blurred observation.
Abstract
We present a scheme for recovering the orientation of a planar scene from a single translation ally-motion blurred image. By leveraging the homography relationship among image coordinates of 3D points lying on a plane, and by exploiting natural correspondences among the extremities of the blur kernels derived from the motion blurred observation, the proposed method can accurately infer the normal of the planar surface. We validate our approach on synthetic as well as real planar scenes.

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Citations
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Proceedings ArticleDOI

From Local to Global: Edge Profiles to Camera Motion in Blurred Images

TL;DR: This work investigates the relation between the edge profiles present in a motion blurred image and the underlying camera motion responsible for causing the motion blur and incorporates a suitably derived constraint from edge profiles into an existing blind deblurring framework and demonstrates improved restoration performance.
Posted Content

Planar Geometry and Latest Scene Recovery from a Single Motion Blurred Image

TL;DR: An approach for estimation of normal of a planar scene from a single motion blurred observation and 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 the findings.
Journal Article

Unfolding a blurred image

TL;DR: This work first learns motion representation from sharp videos in an unsupervised manner through training of a convolutional recurrent video autoencoder network that performs a surrogate task of video reconstruction that outperforms competing methods across all factors: accuracy, speed, and compactness.
Proceedings ArticleDOI

Tapping motion blur for robust normal estimation of planar scenes

TL;DR: A framework for robust estimation of normal of a planar scene from a single motion blurred observation is proposed and how feature points can be extracted from blur kernels and matched to generate several point correspondences is revealed.
Proceedings ArticleDOI

Cueing motion blur for registration of inclined planar scenes

TL;DR: This work extends the state-of-the-art by cueing motion blur itself to infer plane inclination by matching extremities of blur kernels computed at different locations in the image by showing that it is possible to find the orientation.
References
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Journal ArticleDOI

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TL;DR: This work introduces a method to remove the effects of camera shake from seriously blurred images, which assumes a uniform camera blur over the image and negligible in-plane camera rotation.
Journal ArticleDOI

High-quality motion deblurring from a single image

TL;DR: A new algorithm for removing motion blur from a single image is presented using a unified probabilistic model of both blur kernel estimation and unblurred image restoration and is able to produce high quality deblurred results in low computation time.
Journal ArticleDOI

A method for enforcing integrability in shape from shading algorithms

TL;DR: An approach for enforcing integrability, a particular implementation of the approach, an example of its application to extending an existing shape-from-shading algorithm, and experimental results showing the improvement that results from enforcingIntegrability are presented.
Book ChapterDOI

Two-phase kernel estimation for robust motion deblurring

TL;DR: It is found that strong edges do not always profit kernel estimation, but instead under certain circumstance degrade it, which leads to a new metric to measure the usefulness of image edges in motion deblurring and a gradient selection process to mitigate their possible adverse effect.
Journal ArticleDOI

Non-uniform Deblurring for Shaken Images

TL;DR: A new parametrized geometric model of the blurring process in terms of the rotational motion of the camera during exposure is proposed, able to capture non-uniform blur in an image due to camera shake using a single global descriptor, and can be substituted into existing deblurring algorithms with only small modifications.