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2020 International Conference on Culture-Oriented Science and technology, ICCST 2020

作者： Su, Zhi-Bin Liu, Bing Zhang, Li-Jing Ren, Hui Communication University of China School of Information and Communication Engineering China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture and Tourism Beijing China

ISBN: (纸本)9781728181387

With the rapid development of intelligent image processing and computer vision, interpreting and extracting emotion information from images have become a hot research topic, especially the studies on film and television scene images with rich expressions and certain feelings from the aspect of audience. To investigate the distribution of emotions and its affect on the result of machine learning, this paper established the emotion classification models with different salient and non-salient regions based on self-built dataset from film and television works. Three salient extraction algorithms were used to the regional segmentation, and the color and texture features of each region were extracted. Emotion classification models were established based on SVM and RF algorithms respectively. Since features of the salient region could not cover all the information of the original image, the prediction accuracy of the unprocessed image was the highest. Nevertheless, when models made an error in the emotion prediction of the original image, the experimental results of salient region could get the correct answer under the certain circumstances. Through the analysis, the areas of interest can be used for emotion prediction to reduce the redundancy;however, to make it more accurate, the appropriate salient region extraction algorithm should be selected for different types of images and features. Our study provides data and theoretical guidance for image understanding and retrieval, and it has practical significance for more detailed classification based on the affective sensation. © 2020 IEEE.

关键词： Support vector machines

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Study on the classification of beatbox sounds based on timbre features

Study on the classification of beatbox sounds based on timbr...

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2020 International Conference on Culture-Oriented Science and technology, ICCST 2020

作者： Zhu, Jiaxing Wang, Junping Liu, Jingyu Zhang, Xiaoyi Conservatory of Music Musicology Department China China Ministry of Culture and Tourism Key Laboratory of Acoustic Visual Technology and Intelligent Control System Communication University of China China

ISBN: (纸本)9781728181387

Beatbox is a performance form of vocal percussion, which is gradually favored by people with continuous development in recent years. With the abundance of Beatbox content on the Internet, the research on its automatic classification becomes very significant. In this article, we mainly using machine learning methods, to identify the beatbox timbre. First of all, we collected 900 Beatbox audio materials and constructed a database. Secondly, 14 acoustic parameters of audio material are extracted by the signal processing method. Finally, we used MultilayerPerceptron, SMO, BayesNet, RandomForest in current machine learning to build a training model for BB timbre classification. The Experimental results showed that the model could classify BB timbre well. © 2020 IEEE.

关键词： Machine learning

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Research on emotional space for movie and TV drama videos

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The Journal of China Universities of Posts and Telecommunications 2022年第5期29卷 73-82页

作者： Li Yujie Zhang Jingjing Jiang Wei Wang Chunxiao Key Laboratory of Acoustic Visual Technology and Intelligent Control System Communication University of ChinaBeijing 100024China Beijing Key Laboratory of Modern Entertainment Technology Communication University of ChinaBeijing 100024China School of Information and Communication Engineering Communication University of ChinaBeijing 100024China School of Computer and Cyber Sciences Communication University of ChinaBeijing 100024China

Emotional space refers to a multi-dimensional emotional model that describes a group of subjective feelings or emotions. Since the existing discrete emotional space is mainly aimed at human’s primary emotions, it cannot describe the complex emotions evoked when watching movies. In order to solve this problem, an emotional fusion space for videos was constructed by selecting movies and TV dramas with rich emotional semantics as the research objects. Firstly, emotional words based on movie and TV drama videos are acquired and analyzed by using subjective evaluation and semantic analysis methods. Then, the emotional word vectors obtained from the above analysis are fused, reduced dimension by t-distributed stochastic neighbor embedding(t-SNE) algorithm, and clustered by bisecting K-means clustering algorithm to get a discrete emotional space for movie and TV drama videos. This emotional fusion space can obtain different categories by changing the value of the emotion classification number without re-labeling and calculation.

关键词： emotional space movie and TV drama videos subjective evaluation words semantic analysis fusion space

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DTMC-Based Performance Evaluation of Mobile-phone User's Application Node 17

DTMC-Based Performance Evaluation of Mobile-phone User's App...

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17th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2018

作者： Wang, Danyu Shi, Minyong Wang, Yongbin Hong, Zhiguo School of Computer Communication University of China Beijing100024 China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture China Beijing Key Laboratory of Modern Entertainment Technology Beijing100024 China

ISBN: (纸本)9781538658925

New media news client now largely replaces traditional newspaper media. Mobile-phone application node is the key component of distributed mobile phone, which offers reading newspaper on mobile phone. The performance mobile-phone application node has great impact on telephone user's experience. This paper uses DTMC-based model checking methodology to evaluate mobile-phone application node's performance such as Sina or Tencent News client. Based on the analysis of news node's working process, the probability of steady-state is chosen as the performance index to study different parameters' influence on it. Furthermore, trend that the probability of steady-state of News node varies with the effect of probability from WeChat state to Weibo state and probability from Game state to Video state is derived thereby. © 2018 IEEE.

关键词： Model checking

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Simulation of stage dry ice effect based on UE4 6

Simulation of stage dry ice effect based on UE4

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6th International Symposium on Computer and Information Processing technology, ISCIPT 2021

作者： Li, Yiyang Li, Jiawen Lv, Chaohui University of China School of Information and Communication Engineering Communication Beijing China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture and Tourism Beijing China

ISBN: (纸本)9781665441377

In view of the problem that the dry ice effect simulation on the stage simulation is less, a dry ice effect simulation system including the realistic rendering module of dry ice effect and the interaction module between actors and the dry ice is proposed. For visual effect of dry ice, this paper uses a method to simulate volume fog in real time by adding visual optimization of multiple noise mixtures. Firstly, in order to solve the problem that the modeling effect of single noise fog is not natural, the Perlin noise and Worley noise are used to model the fog together to enhance the detail and flip effect of fog. Secondly, using the offset shadow algorithm to simulate the self-shadow effect, combining pixel jitter and Temporal oversampling, the soft effect of fog is increased, and the distance field shadow is added to reflect the occlusion. For dry ice interaction module, this paper uses symbol distance field to detect the collision between dry ice and actors to realize the dynamic interaction between actors and dry ice. The results show that this method can simulate the dry ice effect of stage and has the function of real-time interaction. © 2021 IEEE.

关键词： Ice

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Music emotion prediction based on multidimensional feature fusion 3

Music emotion prediction based on multidimensional feature f...

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3rd IEEE International Conference on Information technology, Big Data and Artificial Intelligence, ICIBA 2023

作者： Zhou, Xuanye Su, Zhibin Ren, Hui Communication University of China School of Information and Communication Engineering Beijing China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture and Tourism Beijing China

ISBN: (纸本)9781665490788

Audience sentiment analysis is a popular research task in Music Information Retrieval (MIR). In this work, we aim to lean the prediction model of fine-grained music emotion for intelligent editing and retrieval. To satisfy the properties of time-series of music, the RNN-based model of BILSTM was selected as the bone. In particular, the traditional features and deep features extracted from the CNN architecture of spectrogram was fused with attention mechanism to enhance the recognition ability for different emotions. The ablation experiment has proved the necessary of the multi-dimensional features. Finally, the contrasting experiments on recent algorithms demonstrate that our proposed method for emotion prediction is effective, which is also suitable for small data sets. © 2023 IEEE.

关键词： Forecasting

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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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2024 International Conference on Culture-Oriented Science and technology, CoST 2024

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

ISBN: (纸本)9798350380347

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. © 2024 IEEE.

关键词： Prediction models

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Vehicle object detection based on rgb-camera and radar sensor fusion

Vehicle object detection based on rgb-camera and radar senso...

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2019 International Joint Conference on Information, Media, and Engineering, IJCIME 2019

作者： Li, ZhongTong Yan, Ming Jiang, Wei Xu, Pin 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: (纸本)9781728155869

Object detection has always played a major role in the field of computer vision. With the development of faster region-based convolutional neural network (faster-RCNN), single shot multi-box detector (SSD), You Only Look Once (Yolo) and other deep learning networks, 2D object detection has been developed well developed. However, in some key areas, such as driverless vehicles and artificial intelligence robots, cannot meet the requirements of tasks just by detecting two dimensional (2D) objects. So we need to get the three dimensional (3D) position of the object. In 3D object detection, it is difficult to obtain object position information only by red-green-blue (RGB) image. There are some methods to get the 3D position of the target through the point cloud data set. Therefore, this paper proposes a deep learning network, which can combine both color image information and point cloud geometry information, while using MobileNet V3 as the backbone network greatly enhances the operation speed. The region proposal networks (RPN) layer in faster-RCNN is migrated to the network. After testing, the method proposed by us improves obviously in speed and recognition accuracy compared with the previous methods. © 2019 IEEE.

关键词： Object detection

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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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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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2024 International Conference on Culture-Oriented Science and technology, CoST 2024

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

ISBN: (纸本)9798350380347

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. © 2024 IEEE.

关键词： Virtual environments

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