moving object
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Author(s):  
Ali YAHYAOUY ◽  
Abdelouahed Sabri ◽  
Fadwa BENJELLOUN ◽  
Imane EL MANAA ◽  
Abdellah AARAB

2022 ◽  
pp. 1-12
Author(s):  
Md Rajib M Hasan ◽  
Noor H. S. Alani

Moving or dynamic object analysis continues to be an increasingly active research field in computer vision with many types of research investigating different methods for motion tracking, object recognition, pose estimation, or motion evaluation (e.g. in sports sciences). Many techniques are available to measure the forces and motion of the people, such as force plates to measure ground reaction forces for a jump or running sports. In training and commercial solution, the detailed motion of athlete's available motion capture devices based on optical markers on the athlete's body and multiple calibrated fixed cameras around the sides of the capture volume can be used. In some situations, it is not practical to attach any kind of marker or transducer to the athletes or the existing machinery are being used, while it is required by a pure vision-based approach to use the natural appearance of the person or object. When a sporting event is taking place, there are opportunities for computer vision to help the referee and other personnel involved in the sports to keep track of incidents occurring, which may provide full coverage and analysis in details of the event for sports viewers. The research aims at using computer vision methods, specially designed for monocular recording, for measuring sports activities, such as high jump, wide jump, or running. Just for indicating the complexity of the project: a single camera needs to understand the height at a particular distance using silhouette extraction. Moving object analysis benefits from silhouette extraction and this has been applied to many domains including sports activities. This paper comparatively discusses two significant techniques to extract silhouettes of a moving object (a jumping person) in monocular video data in different scenarios. The results show that the performance of silhouette extraction varies in dependency on the quality of used video data.


Author(s):  
Mritunjay Rai ◽  
Rohit Sharma ◽  
Suresh Chandra Satapathy ◽  
Dileep Kumar Yadav ◽  
Tanmoy Maity ◽  
...  

Author(s):  
Yi Lu ◽  
Zefeng Chang ◽  
Nijia Ye

When a heavy object is cooperatively grasped to move by several fingers of the robot hybrid hand, the inertial properties and the mass distribution of the object must influence largely on the operation precision, grasping stability, and the safety of both the hybrid hand and the object. Hence, it is an important and significant issue to establish and analyze the dynamics model of the moving-object cooperatively grasped by the hybrid hand in order to ensure the safety and grasping stability of the hybrid hand and the object. However, this research has not been conducted. In this paper, a dynamics model of the moving-object grasped by the hybrid hand is established, and its dynamics is studied and analyzed. First, a three-dimensional model of a hybrid hand formed by a novel parallel manipulator and three fingers is designed for cooperatively grasping object. Second, the kinematic formulas for solving the Jacobian matrices, the Hessian matrices, the general velocity/acceleration of the moving platform, and four active limbs of the parallel manipulator are derived. Third, the composite Jacobian matrix and the composite Hessian matrix of the hybrid hand are derived, and the general velocity/acceleration of the moving-object grasped by the hybrid hand is derived. Fourth, dynamics model of the hybrid hand is established, the formulas for solving the dynamic actuation forces of the three fingers and the dynamic actuation forces/torque and constrained forces of the parallel manipulator are derived. Finally, the theoretical solutions of the dynamics model of the moving-object grasped by the hybrid hand are verified by its simulation mechanism.


2021 ◽  
Vol 12 (1) ◽  
pp. 252
Author(s):  
Ke Wu ◽  
Min Li ◽  
Lei Lu ◽  
Jiangtao Xi

The reconstruction of moving objects based on phase shifting profilometry has attracted intensive interests. Most of the methods introduce the phase shift by projecting multiple fringe patterns, which is undesirable in moving object reconstruction as the errors caused by the motion will be intensified when the number of the fringe pattern is increased. This paper proposes the reconstruction of the isolated moving object by projecting two fringe patterns with different frequencies. The phase shift required by the phase shifting profilometry is generated by the object motion, and the model describing the motion-induced phase shift is presented. Then, the phase information in different frequencies is retrieved by analyzing the influence introduced by movement. Finally, the mismatch on the phase information between the two frequencies is compensated and the isolated moving object is reconstructed. Experiments are presented to verify the effectiveness of the proposed method.


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