2022 International Conference on Culture-Oriented Science and Technology (CoST)最新文献_第2页

Automatic Image Generation of Peking Opera Face using StyleGAN2 基于StyleGAN2的京剧脸谱图像自动生成

2022 International Conference on Culture-Oriented Science and Technology (CoST) Pub Date : 2022-08-01 DOI: 10.1109/CoST57098.2022.00030

Xiaoyu Xin, Yinghua Shen, Rui Xiong, Xiahan Lin, Ming Yan, Wei Jiang

引用次数: 0

A Vision Enhancement Network for Image Quality Assessment 用于图像质量评估的视觉增强网络

2022 International Conference on Culture-Oriented Science and Technology (CoST) Pub Date : 2022-08-01 DOI: 10.1109/cost57098.2022.00032

Xinyu Jiang, Jiangbo Xu, Ruoyu Zou

引用次数: 0

Real-time Human-Music Emotional Interaction Based on Multimodal Analysis 基于多模态分析的实时人-音乐情感交互

2022 International Conference on Culture-Oriented Science and Technology (CoST) Pub Date : 2022-08-01 DOI: 10.1109/cost57098.2022.00020

Tianyue Jiang, Sanhong Deng, Peng Wu, Haibi Jiang

引用次数: 0

Research on the practical path of Chinese movie and television communication from the perspective of “The Belt and Road” “一带一路”视角下的中国影视传播实践路径研究

2022 International Conference on Culture-Oriented Science and Technology (CoST) Pub Date : 2022-08-01 DOI: 10.1109/cost57098.2022.00047

Jinchu Zhou, Ying Wang, Bo Li

{"title":"Research on the practical path of Chinese movie and television communication from the perspective of “The Belt and Road”","authors":"Jinchu Zhou, Ying Wang, Bo Li","doi":"10.1109/cost57098.2022.00047","DOIUrl":"https://doi.org/10.1109/cost57098.2022.00047","url":null,"abstract":"Under the background of The Belt and Road Chinese movies face a dual context of coexistence of opportunities and difficulties in international communication. To explore the feasible method of Chinese movie’s external diffusion, we take 36 countries along the “Belt and Road” from 2017.12 to 2020.12 as the research object and use the Latent Dirichlet allocation topic model(LDA) to summarize six categories of topics. According to the box office distribution of each topic, all countries are divided into six categories, and we discuss the topic preferences of each country separately. To promote movie diffusion, for regions with significant cultural differences, the movie should be carried out according to their preferred topics; for regions with better development of the movie market but less cooperation, we should output high-quality local movies to carry out cooperation shooting at the same time; for regions with deep cultural exchanges and a weak economy, we should output movies with diverse culture and preaching national spirit. In addition, it is necessary to consider multiple factors such as the political and religious background to avoid breaking group taboos and formulate export plans according to local conditions to achieve multi-ethnic and multicultural integration further.","PeriodicalId":135595,"journal":{"name":"2022 International Conference on Culture-Oriented Science and Technology (CoST)","volume":"279 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122937014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Performance Evaluation of Multi-Access Based on ATSSS Rules 基于ATSSS规则的多址性能评价

2022 International Conference on Culture-Oriented Science and Technology (CoST) Pub Date : 2022-08-01 DOI: 10.1109/CoST57098.2022.00086

Xinran Ba, Libiao Jin, Zhou Li, Chang Liu, Sidong Li

引用次数: 0

A real-time localization algorithm based on feature point matching 基于特征点匹配的实时定位算法

2022 International Conference on Culture-Oriented Science and Technology (CoST) Pub Date : 2022-08-01 DOI: 10.1109/CoST57098.2022.00056

Shuo Lei, Siyi Tian, Qiming Huang, Anyi Huang

引用次数: 0

Evaluation of Auditory Saliency Model Based on Saliency Map 基于显著性图的听觉显著性模型评价

2022 International Conference on Culture-Oriented Science and Technology (CoST) Pub Date : 2022-08-01 DOI: 10.1109/CoST57098.2022.00061

Xiansong Xiong, Zhijun Zhao, Lingyun Xie

{"title":"Evaluation of Auditory Saliency Model Based on Saliency Map","authors":"Xiansong Xiong, Zhijun Zhao, Lingyun Xie","doi":"10.1109/CoST57098.2022.00061","DOIUrl":"https://doi.org/10.1109/CoST57098.2022.00061","url":null,"abstract":"For the bottom-up auditory attention process, many auditory attention models have been proposed, including the earliest four auditory saliency models developed from visual saliency models, namely Kayser model, Kalinli model, Duangudom model and Kaya model. In order to compare the correlation between the output results of the four models and subjective perception, firstly the four models were evaluated by carrying out a subjective saliency evaluation experiment in this paper. In the subjective evaluation experiment, 20 kinds of sound scene materials were scored with relative saliency and absolute saliency, and two rankings were obtained. Secondly in the saliency model, the saliency scores were calculated for the same 20 kinds of sounds, and the saliency of the sounds were scored by extracting the mean, peak, variance and dynamic characteristics of the saliency score of each sound, and then correlations were calculated between model saliency scores and two subjective scores. The conclusion was that Kalinli model had the best effect among the four models and had the highest correlation with subjective perception; among the four features of the saliency score, the variance had the highest correlation with subjective perception. The main reason for the better results of Kalinli model was that the method of extracting auditory spectrograms and features was more consistent with the auditory characteristics of human ear and the extracted features were more comprehensive. By analyzing the structure and perceptual features of the models with high correlation between model output and subjective perception, we can improve the models in the future based on the conclusions drawn, so as to enhance their performance and make them more consistent with the auditory characteristics of the human ear.","PeriodicalId":135595,"journal":{"name":"2022 International Conference on Culture-Oriented Science and Technology (CoST)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133406105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Development of VR Motion Sickness Test Platform Based on UE 基于UE的VR晕动病测试平台的开发

2022 International Conference on Culture-Oriented Science and Technology (CoST) Pub Date : 2022-08-01 DOI: 10.1109/CoST57098.2022.00043

Yixin Tai, Yu Yang, Xiaotian Wang

引用次数: 2

Performance comparison of deep learning methods on hand bone segmentation and bone age assessment 深度学习方法在手部骨分割和骨龄评估中的性能比较

2022 International Conference on Culture-Oriented Science and Technology (CoST) Pub Date : 2022-08-01 DOI: 10.1109/CoST57098.2022.00083

Yingying Lv, Jingtao Wang, Wenbo Wu, Yun Pan

{"title":"Performance comparison of deep learning methods on hand bone segmentation and bone age assessment","authors":"Yingying Lv, Jingtao Wang, Wenbo Wu, Yun Pan","doi":"10.1109/CoST57098.2022.00083","DOIUrl":"https://doi.org/10.1109/CoST57098.2022.00083","url":null,"abstract":"Bone age is the biological age that reflects the growth and development of human body. Bone age assessment has been applied and plays an important role in clinical medicine, sports science and justice. Reasonable convolution neural network (CNN) models can greatly improve the accuracy and efficiency of bone age assessment. By comparing various hand bone segmentation models trained by classical convolutional neural networks, we found that with intersection over inion (IoU) and dice similarity coefficient (Dice) as evaluation indexes, the segmentation model trained by U-Net had the best performance. Its IoU reached 0.9746, and its Dice reached 0.9871. This is contrary to our inherent recognition that the U-Net++ model is superior to the U-Net model. Based on the images segmented by U-Net, we applied five kinds of common convolutional neural networks to bone age prediction, with mean absolute error (MAE) and error accuracy within two years as evaluation indexes. The results showed that the MAE of Xception was 7.635 and the accuracy of errors within two years reached 97.59%. In this paper, we provide an optimal scheme for bone age image segmentation and bone age assessment, and provide a theoretical basis for the design of bone age assessment system.","PeriodicalId":135595,"journal":{"name":"2022 International Conference on Culture-Oriented Science and Technology (CoST)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114734140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Prediction Method for Dimensional Sentiment Analysis of the Movie and TV Drama based on Variable-length Sequence Input 基于变长序列输入的影视剧多维情感分析预测方法

2022 International Conference on Culture-Oriented Science and Technology (CoST) Pub Date : 2022-08-01 DOI: 10.1109/CoST57098.2022.00010

Chunxiao Wang, Jingiing Zhang, Lihong Gan, Wei Jiang

{"title":"A Prediction Method for Dimensional Sentiment Analysis of the Movie and TV Drama based on Variable-length Sequence Input","authors":"Chunxiao Wang, Jingiing Zhang, Lihong Gan, Wei Jiang","doi":"10.1109/CoST57098.2022.00010","DOIUrl":"https://doi.org/10.1109/CoST57098.2022.00010","url":null,"abstract":"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.","PeriodicalId":135595,"journal":{"name":"2022 International Conference on Culture-Oriented Science and Technology (CoST)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116708025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0