Region-Based Static Video Stitching for Reduction of Parallax Distortion
In this paper, we propose a semantic segmentation-based static video stitching method to reduce parallax and misalignment distortion for sports stadium scenes with dynamic foreground objects. First, video frame pairs for stitching are divided into segments of different classes through semantic segme...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-06-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/21/12/4020 |
| _version_ | 1797530582023929856 |
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| author | Keon-woo Park Yoo-Jeong Shim Myeong-jin Lee |
| author_facet | Keon-woo Park Yoo-Jeong Shim Myeong-jin Lee |
| author_sort | Keon-woo Park |
| collection | DOAJ |
| description | In this paper, we propose a semantic segmentation-based static video stitching method to reduce parallax and misalignment distortion for sports stadium scenes with dynamic foreground objects. First, video frame pairs for stitching are divided into segments of different classes through semantic segmentation. Region-based stitching is performed on matched segment pairs, assuming that segments of the same semantic class are on the same plane. Second, to prevent degradation of the stitching quality of plain or noisy videos, the homography for each matched segment pair is estimated using the temporally consistent feature points. Finally, the stitched video frame is synthesized by stacking the stitched matched segment pairs and the foreground segments to the reference frame plane by descending order of the area. The performance of the proposed method is evaluated by comparing the subjective quality, geometric distortion, and pixel distortion of video sequences stitched using the proposed and conventional methods. The proposed method is shown to reduce parallax and misalignment distortion in segments with plain texture or large parallax, and significantly improve geometric distortion and pixel distortion compared to conventional methods. |
| first_indexed | 2024-03-10T10:31:02Z |
| format | Article |
| id | doaj.art-2a6636357f584e1eb7c8e799bad14551 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T10:31:02Z |
| publishDate | 2021-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-2a6636357f584e1eb7c8e799bad145512023-11-21T23:38:05ZengMDPI AGSensors1424-82202021-06-012112402010.3390/s21124020Region-Based Static Video Stitching for Reduction of Parallax DistortionKeon-woo Park0Yoo-Jeong Shim1Myeong-jin Lee2The Information Technology & Mobile Communications Biz., Samsung Electronics, Suwon-si 16677, Gyeonggi-do, KoreaSchool of Electronics and Information Engineering, Korea Aerospace University, Goyang-si 10540, Gyeonggi-do, KoreaSchool of Electronics and Information Engineering, Korea Aerospace University, Goyang-si 10540, Gyeonggi-do, KoreaIn this paper, we propose a semantic segmentation-based static video stitching method to reduce parallax and misalignment distortion for sports stadium scenes with dynamic foreground objects. First, video frame pairs for stitching are divided into segments of different classes through semantic segmentation. Region-based stitching is performed on matched segment pairs, assuming that segments of the same semantic class are on the same plane. Second, to prevent degradation of the stitching quality of plain or noisy videos, the homography for each matched segment pair is estimated using the temporally consistent feature points. Finally, the stitched video frame is synthesized by stacking the stitched matched segment pairs and the foreground segments to the reference frame plane by descending order of the area. The performance of the proposed method is evaluated by comparing the subjective quality, geometric distortion, and pixel distortion of video sequences stitched using the proposed and conventional methods. The proposed method is shown to reduce parallax and misalignment distortion in segments with plain texture or large parallax, and significantly improve geometric distortion and pixel distortion compared to conventional methods.https://www.mdpi.com/1424-8220/21/12/4020video stitchinghomography estimationsemantic segmentationregion-based video stitching |
| spellingShingle | Keon-woo Park Yoo-Jeong Shim Myeong-jin Lee Region-Based Static Video Stitching for Reduction of Parallax Distortion Sensors video stitching homography estimation semantic segmentation region-based video stitching |
| title | Region-Based Static Video Stitching for Reduction of Parallax Distortion |
| title_full | Region-Based Static Video Stitching for Reduction of Parallax Distortion |
| title_fullStr | Region-Based Static Video Stitching for Reduction of Parallax Distortion |
| title_full_unstemmed | Region-Based Static Video Stitching for Reduction of Parallax Distortion |
| title_short | Region-Based Static Video Stitching for Reduction of Parallax Distortion |
| title_sort | region based static video stitching for reduction of parallax distortion |
| topic | video stitching homography estimation semantic segmentation region-based video stitching |
| url | https://www.mdpi.com/1424-8220/21/12/4020 |
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