114 research outputs found
Light Field Blind Motion Deblurring
We study the problem of deblurring light fields of general 3D scenes captured
under 3D camera motion and present both theoretical and practical
contributions. By analyzing the motion-blurred light field in the primal and
Fourier domains, we develop intuition into the effects of camera motion on the
light field, show the advantages of capturing a 4D light field instead of a
conventional 2D image for motion deblurring, and derive simple methods of
motion deblurring in certain cases. We then present an algorithm to blindly
deblur light fields of general scenes without any estimation of scene geometry,
and demonstrate that we can recover both the sharp light field and the 3D
camera motion path of real and synthetically-blurred light fields.Comment: To be presented at CVPR 201
An object-based approach to image/video-based synthesis and processing for 3-D and multiview televisions
This paper proposes an object-based approach to a class of dynamic image-based representations called "plenoptic videos," where the plenoptic video sequences are segmented into image-based rendering (IBR) objects each with its image sequence, depth map, and other relevant information such as shape and alpha information. This allows desirable functionalities such as scalability of contents, error resilience, and interactivity with individual IBR objects to be supported. Moreover, the rendering quality in scenes with large depth variations can also be improved considerably. A portable capturing system consisting of two linear camera arrays was developed to verify the proposed approach. An important step in the object-based approach is to segment the objects in video streams into layers or IBR objects. To reduce the time for segmenting plenoptic videos under the semiautomatic technique, a new object tracking method based on the level-set method is proposed. Due to possible segmentation errors around object boundaries, natural matting with Bayesian approach is also incorporated into our system. Furthermore, extensions of conventional image processing algorithms to these IBR objects are studied and illustrated with examples. Experimental results are given to illustrate the efficiency of the tracking, matting, rendering, and processing algorithms under the proposed object-based framework. © 2009 IEEE.published_or_final_versio
Coded aperture and coded exposure photography : an investigation into applications and methods
This dissertation presents an introduction to the field of computational photography, and provides a survey of recent research. Specific attention is given to coded aperture and coded exposure theory and methods, as these form the basis for the experiments performed
Joint Blind Motion Deblurring and Depth Estimation of Light Field
Removing camera motion blur from a single light field is a challenging task
since it is highly ill-posed inverse problem. The problem becomes even worse
when blur kernel varies spatially due to scene depth variation and high-order
camera motion. In this paper, we propose a novel algorithm to estimate all blur
model variables jointly, including latent sub-aperture image, camera motion,
and scene depth from the blurred 4D light field. Exploiting multi-view nature
of a light field relieves the inverse property of the optimization by utilizing
strong depth cues and multi-view blur observation. The proposed joint
estimation achieves high quality light field deblurring and depth estimation
simultaneously under arbitrary 6-DOF camera motion and unconstrained scene
depth. Intensive experiment on real and synthetic blurred light field confirms
that the proposed algorithm outperforms the state-of-the-art light field
deblurring and depth estimation methods
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