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A Saliency-Guided Method for Automatic Photo Refocusing

Published: 19 August 2016 Publication History

Abstract

With the prevalence of smart phones and pocket cameras, photo refocusing has become a basic editing and processing method for its power in interesting object emphasis and photo beautification. However, existing image refocusing methods can hardly be applied on mobile devices due to its high computational cost or the dependence on expensive hardware like light field camera. In this paper, we present a simple but effective method to perform image refocusing automatically and rapidly. The key of our method lies in the utilization of the characteristics of human visual systems. By leveraging current saliency detection methods, we locate the region of interest for a given photo rapidly. Then we calculate its depth map according to the frames captured before shooting. The original image is softly segmented into layers and blurred with different confusion sizes according to the depth map. At last, the blurred layers are softly combined into a refocused photo. Experimental results demonstrate that our method performs outstandingly both in automatic photo refocusing and computational complexity.

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  • (2020)A minimum barrier distance for multivariate images with applicationsComputer Vision and Image Understanding10.1016/j.cviu.2020.102993(102993)Online publication date: Jun-2020

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Published In

cover image ACM Other conferences
ICIMCS'16: Proceedings of the International Conference on Internet Multimedia Computing and Service
August 2016
360 pages
ISBN:9781450348508
DOI:10.1145/3007669
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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  • Xidian University

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 August 2016

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Author Tags

  1. automatic photo refocusing
  2. depth of field
  3. salient object detection

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  • Research
  • Refereed limited

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ICIMCS'16

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ICIMCS'16 Paper Acceptance Rate 77 of 118 submissions, 65%;
Overall Acceptance Rate 163 of 456 submissions, 36%

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View all
  • (2020)A minimum barrier distance for multivariate images with applicationsComputer Vision and Image Understanding10.1016/j.cviu.2020.102993(102993)Online publication date: Jun-2020

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