New multi‐view human motion capture framework

Wang, Yuan; Xu, Feiyi; Pun, Chi‐Man; Xiao, Wenqi; Nie, Jianhui; Xiong, Jian; Gao, Hao; Xu, Feng

doi:10.1049/iet-ipr.2019.1606

Cited by 3 publications

(4 citation statements)

References 32 publications

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“…According to Figure 6, the motion accuracy of literature [4] method is 0.183, the motion accuracy of literature [5] method is 0.178, the motion accuracy of literature [6] method is 0.186, the motion accuracy of literature [7] method is 0.176, the motion accuracy of literature [1] method is 0.186, and the motion accuracy of the method in this paper is 0.195. It can be seen that the snowboarding motion using the method in this paper has high accuracy and improves the capture effect.…”

Section: Experimental Indicatorsmentioning

confidence: 78%

“…According to Figure 5, the motion matching ratio of literature [4] method is 1.15, the motion matching ratio of literature [5] method is 1.1, the feature extraction stability of literature [6] method is 1.05, the motion matching ratio of literature [7] method is 1, the motion matching ratio of literature [1] method is 0.9, and the motion matching ratio of the method in this paper is 1.2. Therefore, the snowboarding motion matching proportion using the method in this paper is better and more practical.…”

Section: Experimental Indicatorsmentioning

confidence: 85%

“…On this basis, combined with the calculated snowboarding motion data, the synchronous driving of virtual character motion can be realized. The specific process is divided into the following three steps: The proposed method Literature [4]method Literature [5]method…”

Section: Establishment and Driving Of The Virtual Charactermentioning

confidence: 99%

“…In order to verify the effectiveness of snowboarding athletes' skiing motion real-time capture based on a 3D vision sensor, experimental analysis was carried out. Under the same test conditions, carry out motion capture according to the four methods given in literature [4] to literature [1], and then carry out fine motion comparison, and compare the comparison results with the studied methods. It is shown in Table 2.…”

Section: Experimental Indicatorsmentioning

confidence: 99%

See 3 more Smart Citations

Real‐Time Capture of Snowboarder’s Skiing Motion Using a 3D Vision Sensor

Li¹,

Wang

Tao

et al. 2021

Wireless Communications and Mobile Computing

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Due to the influence of environmental interference and too fast speed, there are some problems in ski motion capture, such as inaccurate motion capture, motion delay, and motion loss, resulting in the inconsistency between the actual motion of later athletes and the motion of virtual characters. To solve the above problems, a real-time skiing motion capture method of snowboarders based on a 3D vision sensor is proposed. This method combines the Time of Fight (TOF) camera and high-speed vision sensor to form a motion acquisition system. The collected motion images are fused to form a complete motion image, and the pose is solved. The pose data is bound with the constructed virtual character model to drive the virtual model to synchronously complete the snowboarding motion and realize the real-time capture of skiing motion. The results show that the motion accuracy of the system is as high as 98.6%, which improves the capture effect, and the motion matching proportion is better and more practical. It is also excellent in the investigation of motion delay and motion loss.

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Section: Experimental Indicatorsmentioning

confidence: 78%

Section: Experimental Indicatorsmentioning

confidence: 85%

Section: Establishment and Driving Of The Virtual Charactermentioning

confidence: 99%

Section: Experimental Indicatorsmentioning

confidence: 99%

See 2 more Smart Citations

Real‐Time Capture of Snowboarder’s Skiing Motion Using a 3D Vision Sensor

Li¹,

Wang

Tao

et al. 2021

Wireless Communications and Mobile Computing

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show abstract

Action capture and VR interactive system for online experimental teaching

Hao,

Cao

2024

Entertainment Computing

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Developing a Framework to Preserve the Intangible Culture and Heritage in the Endemic Era Using Motion Capture as Capturing Tools

Zaman¹

2022

2nd International Conference on Creative Multimedia 2022 (ICCM 2022)

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In this paper, the researcher addresses on developing the framework of preserving the intangible cultural movement that designed as digital preservation. It draws importance of the process of pre production, ethic reviews, and preparation before the cultural movement recording process. The researcher signifies the needs of the framework to differ the capturing cultural movement comparing the normal capturing process using motion capture suite.

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New multi‐view human motion capture framework

Cited by 3 publications

References 32 publications

Real‐Time Capture of Snowboarder’s Skiing Motion Using a 3D Vision Sensor

Real‐Time Capture of Snowboarder’s Skiing Motion Using a 3D Vision Sensor

Action capture and VR interactive system for online experimental teaching

Developing a Framework to Preserve the Intangible Culture and Heritage in the Endemic Era Using Motion Capture as Capturing Tools

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