RGBD Scene Flow Estimation with Global Nonrigid and Local Rigid Assumption
RGBD scene flow has attracted increasing attention in the computer vision with the popularity of depth sensor. To estimate the 3D motion of object accurately, a RGBD scene flow estimation method with global nonrigid and local rigid motion assumption is proposed in this paper. Firstly, the preprocess...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2020/8215389 |
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| _version_ | 1832556880029810688 |
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| author | Xiuxiu Li Yanjuan Liu Haiyan Jin Lei Cai Jiangbin Zheng |
| author_facet | Xiuxiu Li Yanjuan Liu Haiyan Jin Lei Cai Jiangbin Zheng |
| author_sort | Xiuxiu Li |
| collection | DOAJ |
| description | RGBD scene flow has attracted increasing attention in the computer vision with the popularity of depth sensor. To estimate the 3D motion of object accurately, a RGBD scene flow estimation method with global nonrigid and local rigid motion assumption is proposed in this paper. Firstly, the preprocessing is implemented, which includes the colour-depth registration and depth image inpainting, to processing holes and noises in the depth image; secondly, the depth image is segmented to obtain different motion regions with different depth values; thirdly, scene flow is estimated based on the global nonrigid and local rigid assumption and spatial-temporal correlation of RGBD information. In the global nonrigid and local rigid assumption, each segmented region is divided into several blocks, and each block has a rigid motion. With this assumption, the interaction of motion from different parts in the same segmented region is avoided, especially the nonrigid object, e.g., a human body. Experiments are implemented on RGBD tracking dataset and deformable 3D reconstruction dataset. The visual comparison shows that the proposed method can distinguish the motion parts from the static parts in the same region better, and the quantitative comparisons proved more accurate scene flow can be obtained. |
| format | Article |
| id | doaj-art-435e32adea4942a390ab355701725554 |
| institution | Kabale University |
| issn | 1026-0226 1607-887X |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-435e32adea4942a390ab3557017255542025-02-03T05:44:12ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2020-01-01202010.1155/2020/82153898215389RGBD Scene Flow Estimation with Global Nonrigid and Local Rigid AssumptionXiuxiu Li0Yanjuan Liu1Haiyan Jin2Lei Cai3Jiangbin Zheng4Xi’an University of Technology, Xi’an 710048, ChinaXi’an University of Technology, Xi’an 710048, ChinaXi’an University of Technology, Xi’an 710048, ChinaXi’an University of Technology, Xi’an 710048, ChinaNorthwestern Polytechnical University, Xi’an 710029, ChinaRGBD scene flow has attracted increasing attention in the computer vision with the popularity of depth sensor. To estimate the 3D motion of object accurately, a RGBD scene flow estimation method with global nonrigid and local rigid motion assumption is proposed in this paper. Firstly, the preprocessing is implemented, which includes the colour-depth registration and depth image inpainting, to processing holes and noises in the depth image; secondly, the depth image is segmented to obtain different motion regions with different depth values; thirdly, scene flow is estimated based on the global nonrigid and local rigid assumption and spatial-temporal correlation of RGBD information. In the global nonrigid and local rigid assumption, each segmented region is divided into several blocks, and each block has a rigid motion. With this assumption, the interaction of motion from different parts in the same segmented region is avoided, especially the nonrigid object, e.g., a human body. Experiments are implemented on RGBD tracking dataset and deformable 3D reconstruction dataset. The visual comparison shows that the proposed method can distinguish the motion parts from the static parts in the same region better, and the quantitative comparisons proved more accurate scene flow can be obtained.http://dx.doi.org/10.1155/2020/8215389 |
| spellingShingle | Xiuxiu Li Yanjuan Liu Haiyan Jin Lei Cai Jiangbin Zheng RGBD Scene Flow Estimation with Global Nonrigid and Local Rigid Assumption Discrete Dynamics in Nature and Society |
| title | RGBD Scene Flow Estimation with Global Nonrigid and Local Rigid Assumption |
| title_full | RGBD Scene Flow Estimation with Global Nonrigid and Local Rigid Assumption |
| title_fullStr | RGBD Scene Flow Estimation with Global Nonrigid and Local Rigid Assumption |
| title_full_unstemmed | RGBD Scene Flow Estimation with Global Nonrigid and Local Rigid Assumption |
| title_short | RGBD Scene Flow Estimation with Global Nonrigid and Local Rigid Assumption |
| title_sort | rgbd scene flow estimation with global nonrigid and local rigid assumption |
| url | http://dx.doi.org/10.1155/2020/8215389 |
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