Dance Movement Learning for Labanotation Generation Based on Motion-Captured Data

Li, Min; Zhang, Miao; Ma, Cong

doi:10.1109/access.2019.2951588

Cited by 19 publications

(10 citation statements)

References 36 publications

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“…This could lighten the workload. [1] The analysis proceeds the evolution of a DL system for diverse SL union, conversion, and identification. They decrypt the affair that accompanied by preceding SL characterization and recording synthesis methods by utilizing the recommended H-DNA architecture.…”

Section: Literature Surveymentioning

confidence: 99%

A Review on Dynamic Hand Gesture Recognition Techniques

A¹,

Harish²,

Sambhrama³

et al. 2023

IJRASET

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Body language is one of the nonverbal methodsof communication, and it comprises hand gestures, arm movements, posturing, and gestures and facial expressions. One way to communicate information through the movement of the body is through gestures. HGR is a smart, intuitive, and easy method of human-computer interaction (HCI). HGR systems have two key applications: SLR and GBC. To help the deaf communicate with the hearing community, SLR tries to automaticallyinterpret SLs via a computer. The idea that SL is a highly ordered and primarily symbolic collection of human gestures is what led to the development of universal gesture-based HCI.

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Section: Literature Surveymentioning

confidence: 99%

A Review on Dynamic Hand Gesture Recognition Techniques

A¹,

Harish²,

Sambhrama³

et al. 2023

IJRASET

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show abstract

“…The goal of the third one is to weaken the influence of different shapes of people. The fourth feature normalizes the orientation of human body for the relative vectors of the [1], [3], [4], [8], [32], [36] and the proposed one on recognition accuracy based on dataset A.…”

Section: ) Evaluation Of the Featurementioning

confidence: 99%

“…For lower limb, the compared methods include rulebased method [3], template-based method [6], HMM-based method [32] and three CNN-and LSTM-based methods [33]- [35]. The rule-based and template-based methods belong to the traditional ways.…”

Section: ) Evaluation Of the Movement Analysismentioning

confidence: 99%

Labanotation Generation From Motion Capture Data for Protection of Folk Dance

et al. 2020

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Labanotation is one of the well-known notation systems for the documenting and archiving of human motion. It plays a powerful role in dance protection, choreography analysis, and so on. Recently, researchers are committed to using computer technology to automatically generate Labanotation rather than manually drawing. However, the existing generation methods cannot deal with the various changes in motion data, such as different scales, angles, motion modes and limbs. In this paper, we aim to generate Labanotation from motion capture data acquired through real folk dance performances. The main steps include feature extraction, motion segmentation and unit movement analysis. Firstly, a normalized feature named Lie group feature is extracted, which can cope with the challenges of different scales and angles in motion data. Secondly, in order to divide motion with different modes into unit fragments for further recognizing, we propose a segmentation method that combines the speed threshold and the region partition. Thirdly, to generate Laban symbols of unit movements for different limbs, two kinds of neural networks are used for the analysis. On the one hand, LieNet, a powerful network for analyzing time series data based on Lie group structure, is utilized to recognize the lower limb movements. On the other hand, extreme-learning machine, a single hidden layer feedforward neural network, is used to identify the upper limb postures. Experimental results demonstrate that our method of feature extraction, motion segmentation and unit movement analysis achieves better results than the previous works, which makes the generated Labanotation score more reliable.

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“…Sports social networking meets the social needs of modern young people and brings stable user traffic and large user stickiness to sports APP. Therefore, these sports APP can also refer to some current social media, such as microblog and WeChat, so as to bring formal profits to the emerging market of sports [15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Wearable Running Training Data Acquisition System Based on Intelligent Computer Technology

Liu

Chang

Cao

et al. 2022

Computational and Mathematical Methods in Medicine

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Because the instantaneous motion of running training changes rapidly, the acquisition accuracy is low. Therefore, a wearable running training data acquisition system based on intelligent computer technology is designed. In the hardware design of the system, by setting the registers of the main control chip, inertial sensor, and magnetic sensor, the acceleration and angular velocity information of motion exist in the data format of binary complement. Bluetooth realizes the transparent transmission of data between hardware and software. The system software uses LDA recognition algorithm to decompose the dynamic data transmitted by Bluetooth into multiple static data and collect the final motion data through training. The experimental results show that the designed system has good quality and high accuracy in motion detection and counting.

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Dance Movement Learning for Labanotation Generation Based on Motion-Captured Data

Cited by 19 publications

References 36 publications

A Review on Dynamic Hand Gesture Recognition Techniques

A Review on Dynamic Hand Gesture Recognition Techniques

Labanotation Generation From Motion Capture Data for Protection of Folk Dance

Wearable Running Training Data Acquisition System Based on Intelligent Computer Technology

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