Kinematic target surface sensing based on improved deep optical flow tracking

Abstract

Reconstruction of moving target surfaces based on active image sensing techniques, such as phase-shifting profilometry, has attracted intensive research in recent years. The measurement error caused by object motion can be addressed successfully by tracking the object movement. However, it either requires high-cost color imaging equipment or is limited by the assumption of 2D translation movement. Therefore, this paper proposes what we believe to be a new method to reconstruct the kinematic object surfaces with any 2D movement sensed by affordable monochrome camera. An improved RAFT optical flow algorithm is proposed to track the object based on the object fringe pattern image directly. The feature points on the object are retrieved immune to the fringe pattern illumination. Then, the RANSAC algorithm and an iteration selection process are employed to select feature points with high quality optical flow. At last, the motion is described mathematically, and the dynamic object is reconstructed successfully. Experiments are presented to verify the effectiveness of the proposed method.

Deep Learning-Based Consistent Object Detection in Distance on Highly Perspective Region

“…Nevertheless, OD performance analysis utilizing AP metric demonstrates distance-consistent performance in TI, suggesting that the impact of object size versus sharpness on OD performance is negligible. (4) When identifying the direction and velocity of vehicle movement to detect unexpected accidents like abrupt stops and backward travel of vehicles on tunnel roads, ensuring consistent AV evaluation from CCTV images proves notably beneficial because that phenomenon assists the object tracking of driving vehicles [52]. Nevertheless, a significant discord between AV and actual velocity in OI necessitates intricate algorithmic corrections that account for vehicle distance to prevent false detections.…”

Multi-thread two-dimensional digital image correlation for full-field displacement and rotation angle measurement

“…With the persistent efforts of researchers, since DIC was initially proposed by Peter and Ranson, 4 DIC has obtained great improvement in the aspects of measurement accuracy, computation efficiency, and robustness and become mature now. 5 In addition, DIC has achieved huge successes in wide applications, such as mechanical property testing of material and structure, [6][7][8][9][10] residual stress measurement, 11,12 vibration extraction, 13 and structure health monitoring, [14][15][16] etc. The focus of this study is on the large rotation issue of 2D DIC which is often performed in a system having one camera in the case of a planar test object.…”