Reliable Depth-of-Field Rendering Using Estimated Depth Maps

Whan Choi, Kyung Rae Kim, Chang-Su Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A reliable algorithm for rendering depth of field (DoF) effects using estimated depth maps, obtained through stereo matching, is proposed in this paper. The proposed algorithm generates blurring to simulate images spontaneously seen by human vision systems. We develop two types of windows : circle of confusion (CoC) blurring window and peripheral blurring window. First, the CoC blurring window is determined by comparing the depth values of a gazing point and each sample point. Second, the peripheral blurring window is obtained by calculating the distance between the gazing and sample points. Then, we combine the two windows to make the total blurring window. Finally, through a masking process, we modulate the total blurring window to provide a more natural DoF. Experimental results demonstrate that the proposed algorithm provides realistic blurring, by preserving edges clearly as well as blurring far points from the gazing point effectively.

Original languageEnglish
Title of host publication2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Volume2018-May
ISBN (Electronic)9781538648810
DOIs
Publication statusPublished - 2018 Apr 26
Event2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Florence, Italy
Duration: 2018 May 272018 May 30

Other

Other2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018
CountryItaly
CityFlorence
Period18/5/2718/5/30

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

Choi, W., Kim, K. R., & Kim, C-S. (2018). Reliable Depth-of-Field Rendering Using Estimated Depth Maps. In 2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Proceedings (Vol. 2018-May). [8351453] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISCAS.2018.8351453