.png){kind=icon}
返回
SIFT-aided path-independent digital image correlation accelerated by parallel computing
.png){kind=icon}
PRE
AI
DOI：10.1016/j.optlaseng.2019.105964.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Current iterative digital image correlation (DIC) algorithms can efficiently converge at the deformation vector with high accuracy when they are fed with reliable initial guess. Thus, the adaptability of DIC method is dominated to a large extent by the estimation of initial guess. In recent years, image feature-based technique, especially the scale-invariant feature transform (SIFT), was introduced to DIC for the estimation of initial guess in the case of large and complex deformation, due to its robustness in handling the images with translation, rotation, scaling, and localized distortion. However, feature extraction and matching in SIFT are very time consuming, which limits the applications of the SIFT-aided DIC. In this study, we developed a SIFT-aided path-independent DIC method and accelerated it by introducing the parallel computing on graphics processing unit (GPU) or multi-core CPU. In our method, SIFT features are used to estimate the initial guess for the inverse compositional Gauss-Newton (IC-GN) algorithm at each point of interest (POI). The experimental study shows that the developed method can deal with large and inhomogeneous deformation with high accuracy. Parallel computing (especially on GPU) accelerates significantly the proposed DIC method. The achieved computation speed satisfies the need for real-time processing with high resolution for the images of normal sizes.
Keyword:
Digital image correlation
Initial guess
Scale-invariant feature transform
Parallel computing
Graphics processing unit
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.7
论文数:
7.3K
被引数:
1.7W
机构
引用论文
.png){kind=icon}
The Role of the Levator Ani Muscle in Evacuation, Sexual Performance and Pelvic Floor Disorders
PREAI
分享收藏
查看更多内容