article

Photo-consistent synthesis of motion blur and depth-of-field effects with a real camera model

Authors:

Chia-Hong ChangAuthors Info & Claims

Image and Vision Computing, Volume 30, Issue 9

Pages 605 - 618

https://doi.org/10.1016/j.imavis.2012.07.004

Published: 01 September 2012 Publication History

Abstract

Depth-of-field (DOF) and motion blur are important visual cues used for computer graphics and photography to illustrate focus of attention and object motion. In this work, we present a method for photo-realistic DOF and motion blur generation based on the characteristics of a real camera system. Both the depth-blur relation for different camera focus settings and the nonlinear intensity response of image sensors are modeled. The camera parameters are calibrated and used for defocus and motion blur synthesis. For a well-focused real scene image, DOF and motion blur effects are generated by post-processing techniques. Experiments have shown that the proposed method generates more photo-consistent results than the commonly used graphical models.

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Cited By

Liu JWang ZMa LFang CBai TZhang XLiu JChen Z(2024)Benchmarking Object Detection Robustness against Real-World CorruptionsInternational Journal of Computer Vision10.1007/s11263-024-02096-6132:10(4398-4416)Online publication date: 1-Oct-2024
https://dl.acm.org/doi/10.1007/s11263-024-02096-6
Lopez-Ramirez MLedesma-Carrillo LCabal-Yepez EBotella GRodriguez-Donate CLedesma S(2017)FPGA-based methodology for depth-of-field extension in a single imageDigital Signal Processing10.1016/j.dsp.2017.07.01470:C(14-23)Online publication date: 1-Nov-2017
https://dl.acm.org/doi/10.1016/j.dsp.2017.07.014

Photo-consistent synthesis of motion blur and depth-of-field effects with a real camera model
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision tasks
  2. Computer graphics

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cover image Image and Vision Computing

Image and Vision Computing Volume 30, Issue 9

September, 2012

91 pages

ISSN:0262-8856

Issue’s Table of Contents

Copyright © Elsevier B.V. © 2012.

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Butterworth-Heinemann

United States

Publication History

Published: 01 September 2012

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Cited By

Liu JWang ZMa LFang CBai TZhang XLiu JChen Z(2024)Benchmarking Object Detection Robustness against Real-World CorruptionsInternational Journal of Computer Vision10.1007/s11263-024-02096-6132:10(4398-4416)Online publication date: 1-Oct-2024
https://dl.acm.org/doi/10.1007/s11263-024-02096-6
Lopez-Ramirez MLedesma-Carrillo LCabal-Yepez EBotella GRodriguez-Donate CLedesma S(2017)FPGA-based methodology for depth-of-field extension in a single imageDigital Signal Processing10.1016/j.dsp.2017.07.01470:C(14-23)Online publication date: 1-Nov-2017
https://dl.acm.org/doi/10.1016/j.dsp.2017.07.014

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