scholarly journals High-Speed Accurate 3D Scanning of Human Motion Sequences

Author(s):  
Christian BRAUER BURCHARDT ◽  
Stefan HEIST ◽  
Ingo SCHMIDT ◽  
Peter LUTZKE ◽  
Peter KUHMSTEDT ◽  
...  
Keyword(s):  
Author(s):  
Nathan Tessema Ersumo ◽  
Cem Yalcin ◽  
Nick Antipa ◽  
Nicolas Pegard ◽  
Laura Waller ◽  
...  

Author(s):  
Yi Zheng ◽  
Beiwen Li

Abstract In-situ inspection has drawn many attentions in manufacturing due to the importance of quality assurance. Having an accurate and robust in-situ monitoring can assist corrective actions for a closed-loop control of a manufacturing process. The fringe projection technique, as a variation of the structured light technique, has demonstrated significant potential for real-time in-situ monitoring and inspection given its merits of conducting simultaneous high-speed and high accuracy measurements. However, high-speed 3D scanning methods like fringe projection technique are typically based on triangulation principle, meaning that the depth information is retrieved by analyzing the triangulation relationship between the light emitter (i.e., projector), the image receiver (i.e., camera) and the tested sample surface. Such measurement scheme cannot reconstruct 3D surfaces where large geometrical variations are present, such as a deep-hole or a stair geometry. This is because large geometrical variations will block the auxiliary light used in the triangulation based methods, which will resultantly cause a shadowed area to occur. In this paper, we propose a uniaxial fringe projection technique to address such limitation. We measured a stair model using both conventional triangulation-based fringe projection technique and the proposed method for comparison. Our experiment demonstrates that the proposed uniaxial fringe projection technique can perform high-speed 3D scanning without shadows appearing in the scene. Quantitative testing shows that an accuracy of 1.15% can be obtained using the proposed uniaxial fringe projection system.


2009 ◽  
Vol 20 (12) ◽  
pp. 125101 ◽  
Author(s):  
Yuru Wang ◽  
Jiafeng Liu ◽  
Guojun Liu ◽  
Xianglong Tang ◽  
Peng Liu
Keyword(s):  

2006 ◽  
Vol 10 (2) ◽  
pp. 112-115 ◽  
Author(s):  
Masashi Uchinoumi ◽  
Joo Kooi Tan ◽  
Seiji Ishikawa ◽  
Toru Naito ◽  
Makoto Yokota

2006 ◽  
Vol 18 (5) ◽  
pp. 598-607 ◽  
Author(s):  
Tomoari Maruyama ◽  
◽  
Chunquan Xu ◽  
Aiguo Ming ◽  
Makoto Shimojo

We have developed a golf robot whose swing simulates human motion. The design concept is to realize ultra-high-speed dynamic manipulation using a dexterous mechanism. The robot consists of a shoulder joint with a high-power direct-drive motor and a wrist joint with a low-power direct-drive motor. High-speed golf swings are realized by a sort of motion control, called dynamically-coupled driving which compensates for the lack of drive in the wrist joint. In this paper a new model accounting for golf club flexibility with all parameters identified in experiments was developed. Based on this, we generated and implemented trajectories for different criteria. Experimental results confirmed the high accuracy of motion control and the feasibility of golf club flexibility in ultra-high-speed manipulation.


Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3517 ◽  
Author(s):  
Xiaoyue Zhang ◽  
Wan Xiao

To accurately measure human motion at high-speed, we proposed a simple structure complementary filter, named the Fuzzy Tuned and Second EStimator of the Optimal Quaternion Complementary Filter (FTECF). The FTECF is applicable to inertial and magnetic sensors, which include tri-axis gyroscopes, tri-axis accelerometers, and tri-axis magnetometers. More specifically, the proposed method incorporates three parts, the input quaternion, the reference quaternion, and the fuzzy logic algorithm. At first, the input quaternion was calculated with gyroscopes. Then, the reference quaternion was calculated by applying the Second EStimator of the Optimal Quaternion (ESOQ-2) algorithm on accelerometers and magnetometers. In addition, we added compensation for accelerometers in the ESOQ-2 algorithm so as to eliminate the effects of limb motion acceleration in high-speed human motion measurements. Finally, the fuzzy logic was utilized to calculate the fusion factor for a complementary filter, so as to adaptively fuse the input quaternion with the reference quaternion. Additionally, the overall algorithm design is more simplified than traditional methods. Confirmed by the experiments, using a commercial inertial and magnetic sensors unit and an optical motion capture system, the efficiency of the proposed method was more improved than two well-known methods. The root mean square error (RMSE) of the FTECF was less than 2.2° and the maximum error was less than 5.4°.


Author(s):  
Hyun-Joon Chung ◽  
Goobong Chung ◽  
Yujiang Xiang

Zero moment point (ZMP) is an important balance criterion for human motion planning. An important term in the ZMP formula is the rate of angular momentum (RAM) of each link. It is not trivial to compute this term compared to other terms in ZMP formula. In this paper, we first propose an efficient recursive Lagrangian method for calculating the rate of angular momentum in ZMP. This new approach gives a direct way to calculate the rate of angular momentum for each link. Secondly, we evaluate the effects of RAM in ZMP on human motion predictions for walking and running. These two motions are characterized as low speed and high speed motions respectively. We conclude that it is critical to include RAM in ZMP to predict accurate high speed motion. It has relatively less effect on low speed motion.


2019 ◽  
Vol 8 (3) ◽  
pp. 839-846
Author(s):  
Nur Ayuni Mohamed ◽  
Mohd Asyraf Zulkifley

There is a growing demand for surveillance systems that can detect fall-down events because of the increased number of surveillance cameras being installed in many public indoor and outdoor locations. Fall-down event detection has been vigorously and extensively researched for safety purposes, particularly to monitor elderly peoples, patients, and toddlers. This computer vision detector has become more affordable with the development of high-speed computer networks and low-cost video cameras. This paper proposes moving object detection method based on human motion analysis for human fall-down events. The method comprises of three parts, which are preprocessing part to reduce image noises, motion detection part by using TV-L1 optical flow algorithm, and performance measure part. The last part will analyze the results of the object detection part in term of the bounding boxes, which are compared with the given ground truth. The proposed method is tested on Fall Down Detection (FDD) dataset and compared with Gunnar-Farneback optical flow by measuring intersection over union (IoU) of the output with respect to the ground truth bounding box. The experimental results show that the proposed method achieves an average IoU of 0.92524.


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