TY - GEN
T1 - Disparity Estimation using Light Ray Pair in Stacked 3D Light Field
AU - Jung, Hyunmin
AU - Lee, Hyuk Jae
AU - Rhee, Chae Eun
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Light field (LF) is a concept that defines a number of light rays passing through free space, and creates novel views and estimates three-dimensional (3D) information by combining some of the light rays. Among them, the stacked 3D LF is a structure made by stacking several 3D LFs, and it supports free viewpoint movements over a wide range. However, 3D LF is a relatively simple structure and its use is limited due to insufficient vertical light rays. This paper proposes an effective method for estimating vertical disparity between 3D LFs in a stacked 3D LF. This vertical disparity can be used as key information to release the limitation. The contribution of this paper is as follows. First, this paper defines light ray pair in a stacked 3D LF. Light rays corresponding to light ray pair share the same foreground and background, and there is only vertical disparity. Second, based on light ray pair, this paper proposes an effective image reconstruction for disparity estimation. This method reconstructs the reference image by connecting all light rays that are light ray pair with the target image from the neighboring 3D LF. Since this reference image has only vertical disparity, disparity estimation becomes relatively easy. Additionally, the image-based disparity estimation may damage the continuity of 3D LF, so post-processing is applied to compensate for this. In the experimental results, the proposed method shows a noticeable improvement in objects with large disparity that are close to the camera.
AB - Light field (LF) is a concept that defines a number of light rays passing through free space, and creates novel views and estimates three-dimensional (3D) information by combining some of the light rays. Among them, the stacked 3D LF is a structure made by stacking several 3D LFs, and it supports free viewpoint movements over a wide range. However, 3D LF is a relatively simple structure and its use is limited due to insufficient vertical light rays. This paper proposes an effective method for estimating vertical disparity between 3D LFs in a stacked 3D LF. This vertical disparity can be used as key information to release the limitation. The contribution of this paper is as follows. First, this paper defines light ray pair in a stacked 3D LF. Light rays corresponding to light ray pair share the same foreground and background, and there is only vertical disparity. Second, based on light ray pair, this paper proposes an effective image reconstruction for disparity estimation. This method reconstructs the reference image by connecting all light rays that are light ray pair with the target image from the neighboring 3D LF. Since this reference image has only vertical disparity, disparity estimation becomes relatively easy. Additionally, the image-based disparity estimation may damage the continuity of 3D LF, so post-processing is applied to compensate for this. In the experimental results, the proposed method shows a noticeable improvement in objects with large disparity that are close to the camera.
KW - 3D light field
KW - disparity estimation
KW - epipolar plane image
KW - image-based rendering
UR - http://www.scopus.com/inward/record.url?scp=85138995761&partnerID=8YFLogxK
U2 - 10.1109/AICAS54282.2022.9870014
DO - 10.1109/AICAS54282.2022.9870014
M3 - Conference contribution
AN - SCOPUS:85138995761
T3 - Proceeding - IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2022
SP - 435
EP - 438
BT - Proceeding - IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2022
Y2 - 13 June 2022 through 15 June 2022
ER -