3D SIFT aided path independent digital volume correlation and its GPU acceleration. (January 2021)
- Record Type:
- Journal Article
- Title:
- 3D SIFT aided path independent digital volume correlation and its GPU acceleration. (January 2021)
- Main Title:
- 3D SIFT aided path independent digital volume correlation and its GPU acceleration
- Authors:
- Yang, Junrong
Huang, Jianwen
Jiang, Zhenyu
Dong, Shoubin
Tang, Liqun
Liu, Yiping
Liu, Zejia
Zhou, Licheng - Abstract:
- Highlights: A novel 3D SIFT aided path independent DVC method is proposed. The DVC method demonstrate outstanding adaptability to deal with large and complex deformation. The DVC method is accelerated by parallel computing on GPU. Ultrafast computation speed is achieved by of the DVC method on GPU. Abstract: A novel path independent digital volume correlation (DVC) method is proposed, in which the internal deformation field is determined with the aid of the features extracted from the volume images. The deformation vector at each point of interest is first estimated by tracking the motion of the nearby keypoints obtained through 3D scale-invariant feature transform (SIFT), and then fed as the initial guess into the 3D inverse compositional Gauss-Newton algorithm to achieve high accuracy result. Benefiting from the robustness of SIFT to various deformation and distortion of image, the proposed DVC method demonstrates outstanding performance to automatically process the volume images containing large and complex deformation, which keep challenging to current DVC methods for decades. The proposed DVC method is further powered by the parallel computing on GPU. An ultrafast computation speed (about 10, 000 POI/s) can be reached on a personal computer when dealing with the volume images of normal sizes. The 3D SIFT aided DVC method, which achieves unprecedented balance between accuracy, adaptability, and efficiency, shows great potential in the quantitative analysis of internalHighlights: A novel 3D SIFT aided path independent DVC method is proposed. The DVC method demonstrate outstanding adaptability to deal with large and complex deformation. The DVC method is accelerated by parallel computing on GPU. Ultrafast computation speed is achieved by of the DVC method on GPU. Abstract: A novel path independent digital volume correlation (DVC) method is proposed, in which the internal deformation field is determined with the aid of the features extracted from the volume images. The deformation vector at each point of interest is first estimated by tracking the motion of the nearby keypoints obtained through 3D scale-invariant feature transform (SIFT), and then fed as the initial guess into the 3D inverse compositional Gauss-Newton algorithm to achieve high accuracy result. Benefiting from the robustness of SIFT to various deformation and distortion of image, the proposed DVC method demonstrates outstanding performance to automatically process the volume images containing large and complex deformation, which keep challenging to current DVC methods for decades. The proposed DVC method is further powered by the parallel computing on GPU. An ultrafast computation speed (about 10, 000 POI/s) can be reached on a personal computer when dealing with the volume images of normal sizes. The 3D SIFT aided DVC method, which achieves unprecedented balance between accuracy, adaptability, and efficiency, shows great potential in the quantitative analysis of internal deformation. … (more)
- Is Part Of:
- Optics and lasers in engineering. Volume 136(2021)
- Journal:
- Optics and lasers in engineering
- Issue:
- Volume 136(2021)
- Issue Display:
- Volume 136, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 136
- Issue:
- 2021
- Issue Sort Value:
- 2021-0136-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-01
- Subjects:
- Digital volume correlation -- Initial guess -- Scale-invariant feature transform -- Parallel computing -- Graphics processing unit
Lasers in engineering -- Periodicals
Optical measurements -- Periodicals
Optics -- Periodicals
Lasers en ingénierie -- Périodiques
Mesures optiques -- Périodiques
Optique -- Périodiques
621.36605 - Journal URLs:
- http://www.sciencedirect.com/science/journal/01438166 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.optlaseng.2020.106323 ↗
- Languages:
- English
- ISSNs:
- 0143-8166
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6273.443000
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British Library HMNTS - ELD Digital store - Ingest File:
- 22678.xml