An Extended Labanotation Generation Method Based on 3D Human Pose Estimation for Intangible Cultural Heritage Dance Videos

Cai, Xingquan; Li, Rui; Cheng, Pengyan; Yao, Jinzhong; Hu, Yan

doi:10.1142/s0218001423550121

Cited by 3 publications

(1 citation statement)

References 5 publications

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“…CiteSpace scientometric visualization software is applicable to many subject areas in natural and social sciences and is widely used in library intelligence, management, science and technology policy, education, etc [3][4][5][6]. This software can convert a large amount of literature data and present it clearly in the form of graphs [7][8][9]. Therefore, with the help of this software and combined with the traditional literature analysis method, through combing and summarizing its knowledge mapping, we summarize the main vein of Zhuang culture research and discover the deficiencies and future direction, with a view to providing reference and information for the creative transformation and innovative development of Zhuang culture [10][11].…”

Section: Introductionmentioning

confidence: 99%

Citespace-based Research on the Current Situation and Development Trend of the Art of “Sky Jumping” of the Zhuang on the Chinese-Vietnamese Border

Yang,

Chen

2024

Applied Mathematics and Nonlinear Sciences

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China and Vietnam share both land and maritime borders, rendering the exchange and cooperation in ethnic arts along these frontiers crucial for their cultural evolution. This significance underscores the importance of organizing and analyzing the artistic expressions of the Zhuang people, particularly the “Tien Jumping” art form prevalent along the Sino-Vietnamese border. This study introduces an innovative method for text feature expansion utilizing Citespace, integrated with a deep learning-based text classification model, to establish a systematic framework for text classification within this cultural context. Furthermore, acknowledging the multidisciplinary nature of “Tien Jumping” art research, this paper develops a Citespace-based cross-collection system. This system harnesses a thematic network that amalgamates various disciplines to aggregate pertinent data efficiently. Empirical analysis validates the model’s robustness, evidencing an accuracy of 0.95, a recall of 0.87, and an F1 score of 0.91. The investigation into the current state and future trends of “Tien Jumping” research reveals a significant increase in publication volume, from 500 articles in 2013 to 1,108 in 2022— an increment of 608 articles. This growth highlights the strengthening focus on inheritance development, cultural preservation, and the artistry of the Zhuang people, with scores surpassing 7.5 in these emergent research areas. These findings affirm the effectiveness of the proposed methodologies in this study. The approach not only provides a rigorous analysis but also forecasts the trajectory of “Tien Jumping” art research along the Sino-Vietnamese border, offering a scientific foundation for future scholarly inquiries.

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Section: Introductionmentioning

confidence: 99%

Citespace-based Research on the Current Situation and Development Trend of the Art of “Sky Jumping” of the Zhuang on the Chinese-Vietnamese Border

Yang,

Chen

2024

Applied Mathematics and Nonlinear Sciences

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An End-to-End Video Coding Method via Adaptive Vision Transformer

Yang,

Zhou,

Shang

et al. 2024

Int. J. Patt. Recogn. Artif. Intell.

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Deep learning-based video coding methods have demonstrated superior performance compared to classical video coding standards in recent years. The vast majority of the existing deep video coding (DVC) networks are based on convolutional neural networks (CNNs), and their main drawback is that since CNNs are affected by the size of the receptive field, they cannot effectively handle long-range dependencies and local detail recovery. Therefore, how to better capture and process the overall structure as well as local texture information in the video coding task is the core issue. Notably, the transformer employs a self-attention mechanism that captures dependencies between any two positions in the input sequence without being constrained by distance limitations. This is an effective solution to the problem described above. In this paper, we propose end-to-end transformer-based adaptive video coding (TAVC). First, we compress the motion vector and residuals through a compression network built on the vision transformer (ViT) and design the motion compensation network based on ViT. Second, based on the requirement of video coding to adapt to different resolution inputs, we introduce a position encoding generator (PEG) as adaptive position encoding (APE) to maintain its translation invariance across different resolution video coding tasks. The experiment shows that for multiscale structural similarity index measurement (MS-SSIM) metrics, this method exhibits significant performance gaps compared to conventional engineering codecs, such as [Formula: see text], [Formula: see text], and VTM-15.2. We also achieved a good performance improvement compared to the CNN-based DVC methods. In the case of peak signal-to-noise ratio (PSNR) evaluation metrics, TAVC also achieves good performance.

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AIGC Enabling Non-Genetic Design Methods and Practices

Li,

Ma,

et al. 2024

Applied Mathematics and Nonlinear Sciences

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Artificial Intelligence Generated Content (AIGC) technology aligns seamlessly with the design requirements of non-genetic heritage, offering a viable pathway for its modernization. This paper delineates the specific design needs of non-genetic heritage and utilizes a diffusion model to create themed images and animations related to this heritage. Additionally, AIGC is employed to enhance the creation of virtual reality interactive imagery. The Long Short-Term Memory (LSTM) network is deployed to classify time-series gesture data, facilitating the training and categorization of Chinese Sign Language (CSL) gestures for virtual interactive engagement with non-heritage themes. We have integrated the AIGC operation process into the theme of non-genetic inheritance, thereby constructing a robust development trajectory for AIGC-enhanced non-genetic heritage. The experimental setup is crafted to ascertain the optimal number of iterations and training durations through the control variable method. We evaluate the efficacy of the diffusion model for anti-implicit writing analysis and the performance of the speech recognition, text dialogue, and text response modules within the non-heritage multimodal interactive framework using Word Error Rate (WER) and Mean Opinion Score (MOS). A descriptive analysis of users’ interactive experiences with non-heritage content is also conducted. The results indicate that the speech recognition module achieved a WER of 0.365, while the text response module garnered an MOS of 4.49 with a standard deviation of 0.56. This multimodal, non-heritage virtual interaction, leveraging multiple modalities, enriches users’ experiences and deepens their understanding and appreciation of non-heritage content. Consequently, this enhances the high-quality development of non-genetic heritage.

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An Extended Labanotation Generation Method Based on 3D Human Pose Estimation for Intangible Cultural Heritage Dance Videos

Cited by 3 publications

References 5 publications

Citespace-based Research on the Current Situation and Development Trend of the Art of “Sky Jumping” of the Zhuang on the Chinese-Vietnamese Border

Citespace-based Research on the Current Situation and Development Trend of the Art of “Sky Jumping” of the Zhuang on the Chinese-Vietnamese Border

An End-to-End Video Coding Method via Adaptive Vision Transformer

AIGC Enabling Non-Genetic Design Methods and Practices

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