NDLI: Automatic layered RGB-D scene flow estimation with optical flow field constraint

Content Provider	IET Digital Library
Author	Li, Xiuxiu Liu, Yanjuan Jin, Haiyan Zheng, Jiangbin Cai, Lei
Abstract	Scene flow estimation with RGB-D frames is receiving increasing attention in digital video processing and computer vision due to the widespread use of depth sensors. Existing methods based on object segmentation have shown their effectiveness for object occlusion and large displacement. However, improper segmentation often causes incomplete segmented areas or incorrect edges, which will result in inaccurate occlusion inference and scene flow estimation. To this end, an automatic layered RGB-D scene flow estimation method is proposed, which achieves more accurate layering of objects in depth image by exploring motion information. The authors exploit super-pixel segmentation for initial layering, which is beneficial for preserving edges and integrity of the objects. Furthermore, an optical flow which is highly correlated with the scene is also used for automatic layering. Finally, the utilisation of super-pixel segmentation and motion information would ensure the integrity of the object area and improve the accuracy of scene flow. They have validated their approach both qualitatively and quantitatively on several public datasets. Experimental results show that the proposed method is able to preserve the integrity of the object and achieve lower root mean square error and average angular error as compared with the current state-of-the-art algorithms.
Starting Page	4092
Ending Page	4101
Page Count	10
ISSN	17519659
Volume Number	14
e-ISSN	17519667
Issue Number	Issue 16, Dec (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2020.0230
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/14/16
Journal	IET Image Processing
Publisher Date	2020-12-04
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Automatic Layered RGB-D Scene Flow Estimation Automatic Layering Computer Vision Computer Vision And Image Processing Technique Depth Image Digital Video Processing Edge Detection Edge Preservation Image Colour Analysis Image Recognition Image Segmentation Image Sequence Incomplete Segmented Areas Motion Information Object Occlusion Object Segmentation Optical Flow Field Constraint Red Blue Green Depth Frames RGB-D Frames Super-pixel Segmentation Video Signal Processing
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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