Reliable Depth-of-Field Rendering Using Estimated Depth Maps

Whan Choi; Kyung Rae Kim; Chang-Su Kim

doi:10.1109/ISCAS.2018.8351453

Reliable Depth-of-Field Rendering Using Estimated Depth Maps

Whan Choi, Kyung Rae Kim, Chang-Su Kim

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538648810
DOIs	https://doi.org/10.1109/ISCAS.2018.8351453
Publication status	Published - 2018 Apr 26
Event	2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Florence, Italy Duration: 2018 May 27 → 2018 May 30

Publication series

Name	Proceedings - IEEE International Symposium on Circuits and Systems
Volume	2018-May
ISSN (Print)	0271-4310

Other

Other	2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018
Country/Territory	Italy
City	Florence
Period	18/5/27 → 18/5/30

Bibliographical note

Funding Information:
V. CONCLUSIONS We proposed a novel algorithm for DoF rendering, which uses an estimated depth map through CNN-based stereo matching. First, we decide the size and shape of the CoC blurring window and the peripheral blurring window. The CoC blurring window is determined using the estimated depth values. The peripheral blurring window is obtained by calculating the distance between gazing and sample points. Then, we combine the two windows and modulate the result with a mask to provide more natural DoF effects. Experimental results demonstrated that the proposed algorithm outperforms the Zhou’s algorithm [3], yielding better rendering results. ACKNOWLEDGEMENTS This work was supported in part by the National Research Foundation of Korea (NRF) through the Korea Government (MSIP) under Grant NRF-2015R1A2A1A10055037, and in part by ’The Cross-Ministry Giga KOREA Project’ grant funded by the Korea government(MSIT) (No.GK17P0200, Development of 4D reconstruction and dynamic deformable action model based hyper-realistic service technology)

Publisher Copyright:
© 2018 IEEE.

ASJC Scopus subject areas

Electrical and Electronic Engineering

Access to Document

10.1109/ISCAS.2018.8351453

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 Article 8351453 (Proceedings - IEEE International Symposium on Circuits and Systems; Vol. 2018-May). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISCAS.2018.8351453

Reliable Depth-of-Field Rendering Using Estimated Depth Maps. / Choi, Whan; Kim, Kyung Rae; Kim, Chang-Su.
2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. 8351453 (Proceedings - IEEE International Symposium on Circuits and Systems; Vol. 2018-May).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Choi, W, Kim, KR & 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., 8351453, Proceedings - IEEE International Symposium on Circuits and Systems, vol. 2018-May, Institute of Electrical and Electronics Engineers Inc., 2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018, Florence, Italy, 18/5/27. https://doi.org/10.1109/ISCAS.2018.8351453

@inproceedings{e5f444caa7494c848cc5aff1344ac136,

title = "Reliable Depth-of-Field Rendering Using Estimated Depth Maps",

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.",

author = "Whan Choi and Kim, {Kyung Rae} and Chang-Su Kim",

note = "Funding Information: V. CONCLUSIONS We proposed a novel algorithm for DoF rendering, which uses an estimated depth map through CNN-based stereo matching. First, we decide the size and shape of the CoC blurring window and the peripheral blurring window. The CoC blurring window is determined using the estimated depth values. The peripheral blurring window is obtained by calculating the distance between gazing and sample points. Then, we combine the two windows and modulate the result with a mask to provide more natural DoF effects. Experimental results demonstrated that the proposed algorithm outperforms the Zhou{\textquoteright}s algorithm [3], yielding better rendering results. ACKNOWLEDGEMENTS This work was supported in part by the National Research Foundation of Korea (NRF) through the Korea Government (MSIP) under Grant NRF-2015R1A2A1A10055037, and in part by {\textquoteright}The Cross-Ministry Giga KOREA Project{\textquoteright} grant funded by the Korea government(MSIT) (No.GK17P0200, Development of 4D reconstruction and dynamic deformable action model based hyper-realistic service technology) Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 ; Conference date: 27-05-2018 Through 30-05-2018",

year = "2018",

month = apr,

day = "26",

doi = "10.1109/ISCAS.2018.8351453",

language = "English",

series = "Proceedings - IEEE International Symposium on Circuits and Systems",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Proceedings",

}

TY - GEN

T1 - Reliable Depth-of-Field Rendering Using Estimated Depth Maps

AU - Choi, Whan

AU - Kim, Kyung Rae

AU - Kim, Chang-Su

N1 - Funding Information: V. CONCLUSIONS We proposed a novel algorithm for DoF rendering, which uses an estimated depth map through CNN-based stereo matching. First, we decide the size and shape of the CoC blurring window and the peripheral blurring window. The CoC blurring window is determined using the estimated depth values. The peripheral blurring window is obtained by calculating the distance between gazing and sample points. Then, we combine the two windows and modulate the result with a mask to provide more natural DoF effects. Experimental results demonstrated that the proposed algorithm outperforms the Zhou’s algorithm [3], yielding better rendering results. ACKNOWLEDGEMENTS This work was supported in part by the National Research Foundation of Korea (NRF) through the Korea Government (MSIP) under Grant NRF-2015R1A2A1A10055037, and in part by ’The Cross-Ministry Giga KOREA Project’ grant funded by the Korea government(MSIT) (No.GK17P0200, Development of 4D reconstruction and dynamic deformable action model based hyper-realistic service technology) Publisher Copyright: © 2018 IEEE.

PY - 2018/4/26

Y1 - 2018/4/26

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85057117223&partnerID=8YFLogxK

U2 - 10.1109/ISCAS.2018.8351453

DO - 10.1109/ISCAS.2018.8351453

M3 - Conference contribution

AN - SCOPUS:85057117223

T3 - Proceedings - IEEE International Symposium on Circuits and Systems

BT - 2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018

Y2 - 27 May 2018 through 30 May 2018

ER -

Reliable Depth-of-Field Rendering Using Estimated Depth Maps

Abstract

Publication series

Other

Bibliographical note

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this