High-Accuracy Recognition and Localization of Moving Targets in an Indoor Environment Using Binocular Stereo Vision
To obtain effective indoor moving target localization, a reliable and stable moving target localization method based on binocular stereo vision is proposed in this paper. A moving target recognition extraction algorithm, which integrates displacement pyramid Horn–Schunck (HS) optical flow, Delaunay...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-04-01
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| Series: | ISPRS International Journal of Geo-Information |
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| Online Access: | https://www.mdpi.com/2220-9964/10/4/234 |
| _version_ | 1827695773884612608 |
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| author | Jing Ding Zhigang Yan Xuchen We |
| author_facet | Jing Ding Zhigang Yan Xuchen We |
| author_sort | Jing Ding |
| collection | DOAJ |
| description | To obtain effective indoor moving target localization, a reliable and stable moving target localization method based on binocular stereo vision is proposed in this paper. A moving target recognition extraction algorithm, which integrates displacement pyramid Horn–Schunck (HS) optical flow, Delaunay triangulation and Otsu threshold segmentation, is presented to separate a moving target from a complex background, called the Otsu Delaunay HS (O-DHS) method. Additionally, a stereo matching algorithm based on deep matching and stereo vision is presented to obtain dense stereo matching points pairs, called stereo deep matching (S-DM). The stereo matching point pairs of the moving target were extracted with the moving target area and stereo deep matching point pairs, then the three dimensional coordinates of the points in the moving target area were reconstructed according to the principle of binocular vision’s parallel structure. Finally, the moving target was located by the centroid method. The experimental results showed that this method can better resist image noise and repeated texture, can effectively detect and separate moving targets, and can match stereo image points in repeated textured areas more accurately and stability. This method can effectively improve the effectiveness, accuracy and robustness of three-dimensional moving target coordinates. |
| first_indexed | 2024-03-10T12:33:48Z |
| format | Article |
| id | doaj.art-5e1274debfb34ec89e61697ddc1b8d3d |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-03-10T12:33:48Z |
| publishDate | 2021-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-5e1274debfb34ec89e61697ddc1b8d3d2023-11-21T14:25:44ZengMDPI AGISPRS International Journal of Geo-Information2220-99642021-04-0110423410.3390/ijgi10040234High-Accuracy Recognition and Localization of Moving Targets in an Indoor Environment Using Binocular Stereo VisionJing Ding0Zhigang Yan1Xuchen We2School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, ChinaTo obtain effective indoor moving target localization, a reliable and stable moving target localization method based on binocular stereo vision is proposed in this paper. A moving target recognition extraction algorithm, which integrates displacement pyramid Horn–Schunck (HS) optical flow, Delaunay triangulation and Otsu threshold segmentation, is presented to separate a moving target from a complex background, called the Otsu Delaunay HS (O-DHS) method. Additionally, a stereo matching algorithm based on deep matching and stereo vision is presented to obtain dense stereo matching points pairs, called stereo deep matching (S-DM). The stereo matching point pairs of the moving target were extracted with the moving target area and stereo deep matching point pairs, then the three dimensional coordinates of the points in the moving target area were reconstructed according to the principle of binocular vision’s parallel structure. Finally, the moving target was located by the centroid method. The experimental results showed that this method can better resist image noise and repeated texture, can effectively detect and separate moving targets, and can match stereo image points in repeated textured areas more accurately and stability. This method can effectively improve the effectiveness, accuracy and robustness of three-dimensional moving target coordinates.https://www.mdpi.com/2220-9964/10/4/234binocular stereo visionmoving target recognition3D coordinateoptical flowstereo matching |
| spellingShingle | Jing Ding Zhigang Yan Xuchen We High-Accuracy Recognition and Localization of Moving Targets in an Indoor Environment Using Binocular Stereo Vision ISPRS International Journal of Geo-Information binocular stereo vision moving target recognition 3D coordinate optical flow stereo matching |
| title | High-Accuracy Recognition and Localization of Moving Targets in an Indoor Environment Using Binocular Stereo Vision |
| title_full | High-Accuracy Recognition and Localization of Moving Targets in an Indoor Environment Using Binocular Stereo Vision |
| title_fullStr | High-Accuracy Recognition and Localization of Moving Targets in an Indoor Environment Using Binocular Stereo Vision |
| title_full_unstemmed | High-Accuracy Recognition and Localization of Moving Targets in an Indoor Environment Using Binocular Stereo Vision |
| title_short | High-Accuracy Recognition and Localization of Moving Targets in an Indoor Environment Using Binocular Stereo Vision |
| title_sort | high accuracy recognition and localization of moving targets in an indoor environment using binocular stereo vision |
| topic | binocular stereo vision moving target recognition 3D coordinate optical flow stereo matching |
| url | https://www.mdpi.com/2220-9964/10/4/234 |
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