语域(社会语言学)
计算机视觉
图像处理
计算机科学
人工智能
运动(物理)
图像(数学)
运动分析
工程制图
计算机图形学(图像)
工程类
哲学
语言学
作者
Varun Raizada,Harsh Singh Rajput,Mohit Law
标识
DOI:10.1016/j.procir.2023.09.233
摘要
This paper reports on the efficacy of six different image processing schemes to properly resolve cutting tool motion from video. We compare the edge detection and tracking scheme with intensity- and phase-based optical flow-based schemes and with digital image correlation. We also introduce the use of two new schemes: one based on particle image velocimetry (PIV), and another based on the use of convolution neural networks (CNN). Methods are illustrated with video of two tools. Results are benchmarked with twice integrated accelerations. We find that the edge detection and tracking scheme, the PIV scheme, and the CNN scheme are robust.
科研通智能强力驱动
Strongly Powered by AbleSci AI