CASIA OpenIR  > 模式识别国家重点实验室  > 机器人视觉
Elaborate Scene Reconstruction with a Consumer Depth Camera
Li JW(李建伟)1,2; Gao W(高伟)1,2; Wu YH(吴毅红)1,2
Source PublicationInternational Journal of Automation and Computing
2018
Volume15Issue:4Pages:443-453
Abstract
A robust approach to elaborately reconstruct the indoor scene with a consumer depth camera is proposed in this paper. In order to ensure the accuracy and completeness of 3D scene model reconstructed from a freely moving camera, this paper proposes new 3D reconstruction methods, as follows: 1) depth images are processed with a depth adaptive bilateral filter to effectively improve the image quality; 2) a local-to-global registration with the content-based segmentation is performed, which is more reliable and robust to reduce the visual odometry drifts and registration errors; 3) an adaptive weighted volumetric method is used to fuse the registered data into a global model with sufficient geometrical details. Experimental results demonstrate that our approach increases the robustness and accuracy of the geometric models which were reconstructed from a consumer-grade depth camera.
Keyword3d Reconstruction Simultaneous Localization And Mapping (Slam) Volumetric Integration Image Processing Geometry Registration
Indexed ByEI
Language英语
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/23359
Collection模式识别国家重点实验室_机器人视觉
Corresponding AuthorGao W(高伟)
Affiliation1.中国科学院自动化研究所
2.中国科学院大学
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Li JW,Gao W,Wu YH. Elaborate Scene Reconstruction with a Consumer Depth Camera[J]. International Journal of Automation and Computing,2018,15(4):443-453.
APA Li JW,Gao W,&Wu YH.(2018).Elaborate Scene Reconstruction with a Consumer Depth Camera.International Journal of Automation and Computing,15(4),443-453.
MLA Li JW,et al."Elaborate Scene Reconstruction with a Consumer Depth Camera".International Journal of Automation and Computing 15.4(2018):443-453.
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