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Culture-Oriented Science and Technology (CoST), International Conference on

作者： Bowen Liu Wenli Huang Xiumeng Yu Zongliu Ma Ziyi Guo Shuang Wang Wei Jiang State Key Laboratory of Media Convergence and Communication Communication University of China China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Communication University of China China Beijing Key Laboratory of Modern Entertainment Technology Communication University of China China

ISBN: (数字)9798350380347

ISBN: (纸本)9798350380354

The traditional color system of Beijing Forbidden City is comprehensive and complex. The research focuses on collecting color data from the Forbidden City, analyzing subjective and objective color attributes, and compute architectural color image scale. First this research used K-means algorithm to extract the theme color cards of Beijing Forbidden City. Subsequently, single colors were extracted using the idea of community detection, and matching colors were extracted based on the thought of association rule mining. Then this research extracted objective attributes of colors and designed experiments to quantify subjective attributes. Finally, the color subjective and objective data fitting was completed. This outcome is helpful for the digital preservation of traditional colors and the advancement of color culture inheritance practices.

关键词： Costs Image color analysis Urban areas Semantics Fitting Color Data models

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Association Between Timbre Perception Features and Fine-Grained Emotions in Film and Television Music

Association Between Timbre Perception Features and Fine-Grai...

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Culture-Oriented Science and Technology (CoST), International Conference on

作者： Xiaomeng Ren Zhibin Su Wei Jiang Jingyu Liu State Key Laboratory of Media Convergence and Communication (Communication University of China) China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture and Tourism (Communication University of China) China School of Information and Communication Engineering (Communication University of China) China

ISBN: (数字)9798350380347

ISBN: (纸本)9798350380354

As an integral component of modern cultural works, the role of film and television music in artistic expression and emotional communication has become increasingly significant. Timbre, as a crucial attribute of music, has primarily been studied in terms of the influence of its fundamental objective parameters on coarse-grained emotions. However, there is a lack of in-depth exploration of the association between timbre perception features and fine-grained emotion. Consequently, this paper approaches from the perspective of timbre perception features and fine-grained emotions in film and television music. By conducting perceptual evaluation and subjective emotional annotation experiments, it analyzes the correlation between timbre perception features and fine-grained emotions, confirming that timbre perception features significantly influence musical emotions. Furthermore, a multivariate linear regression model was employed to construct a fine-grained emotion prediction model, which has demonstrated good predictive ability for most musical emotions. This research provides a new perspective on understanding the relationship between timbre and emotion in film and television music, offering a scientific basis for its creation and performance.

关键词： TV Costs Correlation Annotations Linear regression Predictive models Timbre

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Research on Visual Cognitive Model Modeling based on Design Psychology

Research on Visual Cognitive Model Modeling based on Design ...

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2022 International Conference on Culture-Oriented Science and Technology, CoST 2022

作者： Hua, Tianyu Wang, Shuang Liu, Jingyu Jiang, Jian State Key Laboratory of Media Convergence and Communication Communication University of China China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture and Tourism China China China Digital Culture Group Co. Ltd China

ISBN: (数字)9781665462488

ISBN: (纸本)9781665462488

This article is based on the theoretical achievements of design psychology, takes graphic poster design as the research object, and combines experimental psychology methods with information processing technology to construct a visual cognitive model that can serve art design. This article firstly starts from the laws of formal beauty in design psychology, and screens the formal beauty features of posters. Secondly, a subjective evaluation experiment for the formal beauty characteristics of the poster materials was conducted, and correlation analysis and factor analysis on the processed experimental data were completed. Finally, this article uses a variety of machine learning algorithms to construct a visual cognitive prediction model. This article summarizes seven low-level and four high-level feature descriptors of the beauty of poster form, and constructs a prediction model from low-level features to high-level features. In addition, this article also quantifies the 'Balance' feature which has the highest word frequency in the low-level features, realizing the calculation of the balance degree of the poster image. © 2022 IEEE.

关键词： Machine learning

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Research on Comfort Perception and Evaluation of Immersive Experience Equipment in Cultural Tourism

Research on Comfort Perception and Evaluation of Immersive E...

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Culture-Oriented Science and Technology (CoST), International Conference on

作者： Huibo Hu Zhibin Su Yujian Jiang Lingxi Qu School of Information and Communication Engineering Communication University of China Beijing China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture and Tourism Beijing China

ISBN: (数字)9798350380347

ISBN: (纸本)9798350380354

Virtual Reality Head-Mounted Display (HMD), also known as VR glasses, is a typical amusement device that provides an immersive viewing experience based on virtual reality technology in cultural tourism equipment. Various factors may cause users to experience different degrees of sensory discomfort when using VR head-mounted displays, posing potential safety risks during performances. This study focuses on typical VR glasses used in cultural tourism performances and evaluates user comfort as the primary indicator. Through subjective evaluation experiment design, it examines the impact of motion conditions, internal scene settings, and VR glasses configuration on users’ comfort perception. The research aims to provide theoretical analysis and experimental data to reduce performance safety risks.

关键词： Performance evaluation Visualization Time-frequency analysis Head-mounted displays Glass Resists Immersive experience

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Fault Prediction Method of Stage Lifts Based on Digital Twin

Fault Prediction Method of Stage Lifts Based on Digital Twin

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Culture-Oriented Science and Technology (CoST), International Conference on

作者： Huiqin Wang Chunxi Zhang Zhen Li Mengjiao Xiao Ministry of Culture and Tourism Key Laboratory of Acoustic Visual Technology and Intelligent Control System Beijing China School of Information and Communication Engineering Communication University of China Beijing China

ISBN: (数字)9798350380347

ISBN: (纸本)9798350380354

To improve the safety of stage lifts’ operation and reduce the failure rate, a digital-twin assisted fault prediction method is proposed here. Signals such as vibration and temperature are collected from the virtual and physical models. A fault prediction model based on Graph Convolutional Networks (GCN) is constructed to identify the potential faults of stage lift. The experiment results illustrate the effectiveness of the proposed model. It would enhance the safety and stability of stage equipment, and provide reliable support for stage performances.

关键词： Fault diagnosis Vibrations Training Computational modeling Predictive models Stability analysis Real-time systems

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Source Separation of Piano Concertos Using Hybrid LSTM-Transformer Model

Source Separation of Piano Concertos Using Hybrid LSTM-Trans...

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Culture-Oriented Science and Technology (CoST), International Conference on

作者： JingYu Liu Wei He Jingjing Zhou Wei Jiang State Key Laboratory of Media Convergence and Communication Beijing China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture and Tourism Beijing China School of Information and Communication Engineering (Communication University of China) Beijing China

ISBN: (数字)9798350380347

ISBN: (纸本)9798350380354

Music source separation, the process of extracting independent audio streams from a complex mix, has traditionally focused on isolating vocals, drums, bass, and other primary sources. This study tackles the more intricate task of separating the piano component from a piano concerto-a challenge compounded by the diverse range of instruments and the dynamic shifts in volume and timbre. Unlike traditional music separation tasks, the piano’s distinct characteristics and its interaction with the orchestra demand a more nuanced *** address the scarcity of multi-track recordings for piano concertos, this research pioneers an artificial data synthesis strategy to create a robust training dataset. We introduce a novel hybrid deep learning model that integrates Long Short-Term Memory (LSTM) networks with Transformer architecture, capitalizing on their complementary strengths to distinguish piano melodies from the rich tapestry of orchestral sounds. Our experiments demonstrate that this hybrid approach significantly outperforms conventional methods, with an improvement of 3.18 dB in signal-to-distortion ratio. These results not only validate the efficacy of proposed method but also pave the way for innovative applications in classical music source separation.

关键词： Training Deep learning Source separation Instruments Transformers Recording Timbre

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Classification of Dunhuang Mural Image Based on Small-sample and Semi-supervised Learning 6

Classification of Dunhuang Mural Image Based on Small-sample...

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6th IEEE Information Technology, Networking, Electronic and Automation control Conference, ITNEC 2023

作者： Cui, Hui Su, Zhibin Zhang, Luyue Bai, Liyang Communication University of China School of Information and Engineering China Key Laboratory of Acoustic Visual Technology and Intelligent Control System China Ministry of Culture and Tourism P.R.C. Center for Ethnic and Folk Literature and Art Development China

ISBN: (纸本)9781665460033

Dunhuang mural images classification belongs to the research task in the field of image recognition. In this paper, the semi-supervised model is established with multidimensional features extracted by transfer learning. A small number of labeled samples were used to obtain a large number of unlabeled data, combined with Active Learning and iterative strategy for multiple rounds of label transfer of selected samples. After several rounds of iterations, we can get a more powerful classification learner. Experiments on the self-built Dunhuang mural dataset have shown that the results can approach or even exceed some supervised learning methods when the number of known label samples is less than 4%. Our research implements the cultural resource image classification algorithm based on small samples, which is conductive to improving the accuracy when label samples are scarce. © 2023 IEEE.

关键词： Image recognition

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A Prediction Method for Dimensional Sentiment Analysis of the Movie and TV Drama based on Variable-length Sequence Input

A Prediction Method for Dimensional Sentiment Analysis of th...

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2022 International Conference on Culture-Oriented Science and Technology, CoST 2022

作者： Wang, Chunxiao Zhang, Jingiing Gan, Lihong Jiang, Wei Key Laboratory of Acoustic Visual Technology and Intelligent Control System Communication University of China Beijing China Zhejiang Dafeng sports equipment Co.Ltd Zhejiang China

ISBN: (数字)9781665462488

ISBN: (纸本)9781665462488

Time continuous emotion prediction problem has always been one of the difficulties in affective video content analysis. The current research mainly designs a temporally continuous long video emotion prediction method by dividing the long video into short video segments of fixed duration. These methods ignore the time dependencies between short video clips and the mood changes in short video clips. Therefore, combined with the related concepts of film and television narrative structure in cinematic language, this paper defines a prediction method for dimensional sentiment analysis of the movie and TV drama based on variable sequence length inputs. First, this paper defines a method for partitioning variable-length audiovisual sequences that set subunits of dimensional emotion prediction as variable sequence-length inputs. Then, a method for extracting and combining audio and visual features of each variable-length audiovisual sequence is proposed. Finally, a prediction network for dimensional emotion is designed based on variable sequence length inputs. This paper focuses on dimensional sentiment prediction and evaluates the proposed method on the extended COGNIMUSE dataset. The method achieves comparable performance to other methods while increasing the prediction speed, with the Mean Square Error (MSE) reduced from 0.13 to 0.11 for arousal and from 0.19 to 0.13 for valence. © 2022 IEEE.

关键词： Sentiment analysis

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Piano Concerto Source Separation Based on Speech Separation and Channel Attention

Piano Concerto Source Separation Based on Speech Separation ...

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Culture-Oriented Science and Technology (CoST), International Conference on

作者： Jingyu Liu JingJing Zhou Xinyan He Wei He State Key Laboratory of Media Convergence and Communication Communication University of China China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture and Tourism Communication University of China China School of Information and Communication Engineering Communication University of China China School of Faculty of International Media Communication University of China China

ISBN: (数字)9798350380347

ISBN: (纸本)9798350380354

The Mossformer model excels in speech separation but has not been effectively applied to music source separation. Music sources have complex characteristics and higher sampling rates, making separation tasks more challenging. We addressed a rarely explored task of separating piano concerto recordings into individual piano and orchestral tracks. This process involves intricate coordination between the piano and orchestra, creating highly complex audio signals in both time and frequency domains. Our main contributions include: (1) adapting the speech separation model for the novel task of piano concerto source separation, constructing and processing a specialized dataset.(2) introducing channel attention in the separation module to dynamically adjust feature focus based on instrument characteristics, enhancing key features. Experiments on the Piano Concerto Dataset (PCD) showed improved separation performance, with a 0.22dB average Signal-to-Distortion Ratio (SDR) increase over the baseline model.

关键词： Adaptation models Source separation Costs Instruments Frequency-domain analysis Speech enhancement Recording

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Image-denoising algorithm based on improved K-singular value decomposition and atom optimization

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CAAI Transactions on Intelligence Technology 2022年第1期7卷 117-127页

作者： Rui Chen Dong Pu Ying Tong Minghu Wu College of Information&Communication Engineering Nanjing Institute of TechnologyNanjingChina College of Electric Power Engineering Nanjing Institute of TechnologyNanjingChina Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System Hubei University of technologyWuhanChina

The traditional K-singular value decomposition(K-SVD)algorithm has poor imagedenoising performance under strong *** image-denoising algorithm is proposed based on improved K-SVD and dictionary atom ***,a correlation coefficient-matching criterion is used to obtain a sparser representation of the image *** dictionary noise atom is detected according to structural complexity and noise intensity and removed to optimize the ***,non-local regularity is incorporated into the denoising model to further improve image-denoising *** of the simulated dictionary recovery problem and application on a transmission line dataset show that the proposed algorithm improves the smoothness of homogeneous regions while retaining details such as texture and edge.

关键词： singular value smoothness

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