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학술지 Minimization of Parallax Artifacts in Video Stitching for Moving Foregrounds
Cited 5 time in scopus Download 6 time Share share facebook twitter linkedin kakaostory
저자
무하마드, 조용주, 서정일
발행일
201810
출처
IEEE Access, v.6, pp.57763-57777
ISSN
2169-3536
출판사
IEEE
DOI
https://dx.doi.org/10.1109/ACCESS.2018.2871685
협약과제
18ZR1100, 초실감 공간미디어 원천기술 개발, 서정일
초록
Parallax handling in the presence of moving foregrounds is a challenging problem in video stitching. The artifacts such as blurring or ghosting become prominent when objects move across multiple views. In this paper, we propose a novel scheme to minimize the parallax artifacts caused by moving objects in a fixed video stitching framework. We first stitch one frame from input videos and generate a lookup table (LUT) for every input video. These LUTs provide the mapping information of input videos to the panorama domain. For every frame of the input videos, we use structural similarity index to identify the LUT points in the overlapping region where parallax exists due to moving object. Therefore, our method does not require to match and track the features across frames to detect the moving object. For every detected LUT point having parallax, a descriptor based on histogram of oriented gradients and local binary patterns is generated and matched such that the parallax is minimized in the overlapping region. This may lead to the undesirable geometric artifacts in the non-overlapping region. To cater this issue, we smoothly propagate the correction in the non-overlapping region closer to the moving object. The proposed scheme is tested on different videos, where the overlapping region is very narrow, ranging from 2.3% to 9%. The experimental results demonstrate that it can significantly reduce the parallax artifacts, which occur due to moving foregrounds.
키워드
Histogram of oriented gradients, local binary patterns, object motion, parallax, video stitching
KSP 제안 키워드
Geometric artifacts, Local binary Pattern, Mapping information, Moving Object, Multiple views, Object motion, Structural SIMilarity index, Structure Similarity Index measure(SSIM), Video Stitching, histogram of oriented gradients, look-up table