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2020 8th International Conference on Digital Home (ICDH)最新文献

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Multi-Scale Recurrent Network for Single Image Deraining 单幅图像分离的多尺度递归网络
2020 8th International Conference on Digital Home (ICDH) Pub Date : 2020-09-01 DOI: 10.1109/ICDH51081.2020.00027
Youxing Li, Rushi Lan, Long Sun, Ji Li, Xiaonan Luo, Cheng Pang
{"title":"Multi-Scale Recurrent Network for Single Image Deraining","authors":"Youxing Li, Rushi Lan, Long Sun, Ji Li, Xiaonan Luo, Cheng Pang","doi":"10.1109/ICDH51081.2020.00027","DOIUrl":"https://doi.org/10.1109/ICDH51081.2020.00027","url":null,"abstract":"Rain streaks noise is one of the greatest influence of outdoor scene tasks. In order to improve the effect of the outdoor scene tasks, we need to reduce the impact of the rain streaks noise while ensuring that other important details are preserved. To handle this issue, we proposed a multi-scale recurrent network (MSReNet) for single image rain removal. By divided MSReNet into two stages: (i) removal rain streaks in the first stage and (ii) restoring background-truth details in the second stage, our network can availably remove huge rain streaks and restore some important background details. Extensive experiments on both synthetic and real images demonstrated that the proposed MSReNet prominently exceeds many recent state-of-the-art methods. Taking the proposed method effectiveness, it is also attractive as a preprocessing process for some visual tasks.","PeriodicalId":210502,"journal":{"name":"2020 8th International Conference on Digital Home (ICDH)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128202188","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 Controllable Spring Force Based Method for Fluid Surface Disturbance Details Simulation 基于可控弹簧力的流体表面扰动细节仿真方法
2020 8th International Conference on Digital Home (ICDH) Pub Date : 2020-09-01 DOI: 10.1109/ICDH51081.2020.00016
Languang Gao, Weina Jiang, Chengying Gao
{"title":"A Controllable Spring Force Based Method for Fluid Surface Disturbance Details Simulation","authors":"Languang Gao, Weina Jiang, Chengying Gao","doi":"10.1109/ICDH51081.2020.00016","DOIUrl":"https://doi.org/10.1109/ICDH51081.2020.00016","url":null,"abstract":"Particle based simulations are widely used in computer graphics. However, few methods use active control for fluid surface. Thus we present a new controllable method based on the spring force model, which provides active control for the disturbance of the fluid surface. This method modifies the spatial distribution of the particles to generate disturbance. To make it controllable, we design a disturbance equation, using the relationship between the macrostate of fluid and the microscopic particles in the Boltzmann’s Entropic Equation. Moreover, we also propose multiple optimizations in order to improve appearance of fluid surface. The correction of fluid splash first detects the target particles by a hybrid method, then adjusts the spring force that acts on these particles. The spring force attenuation model uses a sigmoid function to represent the attenuation of particles at different depths. Experimental results show that our method generates the expected disturbance details. The optimizations enhance the realism of the disturbance simulation.","PeriodicalId":210502,"journal":{"name":"2020 8th International Conference on Digital Home (ICDH)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123241908","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
Underwater high-precision panoramic 3D image generation 水下高精度全景三维图像生成
2020 8th International Conference on Digital Home (ICDH) Pub Date : 2020-09-01 DOI: 10.1109/ICDH51081.2020.00015
Zhaolun Li, Rushi Lan, Zhuo Chen, Xiaonan Luo, Ji Li, Zhiyi Huang, Leiyi Qian
{"title":"Underwater high-precision panoramic 3D image generation","authors":"Zhaolun Li, Rushi Lan, Zhuo Chen, Xiaonan Luo, Ji Li, Zhiyi Huang, Leiyi Qian","doi":"10.1109/ICDH51081.2020.00015","DOIUrl":"https://doi.org/10.1109/ICDH51081.2020.00015","url":null,"abstract":"As an indispensable part of underwater intelligent operations, underwater unmanned system is an important research direction for consolidating China’s ocean security, national defense security, and helping the country’s great strategy of “ marine power “. Its environmental awareness and cognitive capabilities will become an understanding Fundamental and key issues of the ocean and the economic ocean. Existing systems have great deficiencies in underwater perception and detection capabilities, and they cannot all meet the requirements of operations in complex underwater changing environments. This article conducts technical research on the generation of underwater high-definition panoramic 3D data. Therefore, the distributed sonar and binocular vision hybrid system is used as the perception source, and the efficient data access strategy is adopted to update the weight of the corresponding voxel. The integrated low noise high dynamic range chip is used as the imaging terminal, and the underwater optical communication is used to complete many High-precision stereo vision measurement of scenes with point coordination and the generation of refined panoramic 3D data.","PeriodicalId":210502,"journal":{"name":"2020 8th International Conference on Digital Home (ICDH)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123753405","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
Fusing Multi-Features for Rumor tweets detection in Wechat 基于多特征融合的微信谣言检测
2020 8th International Conference on Digital Home (ICDH) Pub Date : 2020-09-01 DOI: 10.1109/ICDH51081.2020.00040
Xiangping Chen, Yingxun Ma, Fan Zhou, Ge Lin, Zhian Zhang
{"title":"Fusing Multi-Features for Rumor tweets detection in Wechat","authors":"Xiangping Chen, Yingxun Ma, Fan Zhou, Ge Lin, Zhian Zhang","doi":"10.1109/ICDH51081.2020.00040","DOIUrl":"https://doi.org/10.1109/ICDH51081.2020.00040","url":null,"abstract":"Recently, rumor detection has attracted lots of research interest because of the quick development of social networks and the widely spread of rumor. The exiting studies is mainly about the open social network such as Weibo and Facebook. However, there is little research about closed social networks, especially Wechat. As a famous app with more than one billion daily active user, the tweets in Wechat can attract lots of attention, which gives the spread of rumor tweets more chance. In this paper, we empirically study the tweets spread in Wechat. We first analyze the text information and users’ behavior of Wechat tweets, then we come up with several important features needed for rumor detection. Furthermore, we propose a new model which can capture the impact of both users’ behavior and text information. We conduct experiments using a large tweets dataset collected in Wechat, the result shows that our proposed method can effectively detect the rumor tweets.","PeriodicalId":210502,"journal":{"name":"2020 8th International Conference on Digital Home (ICDH)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116668669","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
Multi-Deep Features Fusion Algorithm for Clothing Image Recognition 服装图像识别的多深度特征融合算法
2020 8th International Conference on Digital Home (ICDH) Pub Date : 2020-09-01 DOI: 10.1109/ICDH51081.2020.00026
Zhiqiang He, Yuhua Li, Xiayang Shi, Pu Li, Wanwei Huang
{"title":"Multi-Deep Features Fusion Algorithm for Clothing Image Recognition","authors":"Zhiqiang He, Yuhua Li, Xiayang Shi, Pu Li, Wanwei Huang","doi":"10.1109/ICDH51081.2020.00026","DOIUrl":"https://doi.org/10.1109/ICDH51081.2020.00026","url":null,"abstract":"In order to improve recognition accuracy of clothing image and fully exploit the multi-category features extracted from global area, main part, to part areas. This paper utilizes the target detection technology and deep residual network (ResNet) to extract comprehensive clothing features, aims at focusing on clothing itself in the process of extraction procedure, and proposes multi-deep features fusion algorithm for clothing image recognition. First, the YOLOv3 model extracts the global area, main part of clothing and part areas of the image, which forms three category area images, so as to weaken the influence of background and other interference factors. After that, the three category images were sent respectively to improved ResNet for feature extraction, which has been trained beforehand. The ResNet model is improved through optimizing the convolution layer in the residual block, and adjusting the batch normalized layer and the order of the activation function layer, also adjusting the network convolution kernel structure. Finally, the multi-category fusion features were obtained by combining the overall features of the clothing image from the global area, the main part, to the part areas. The experimental results show that the proposed algorithm eliminates the influence of interference factors, makes the recognition process focus on clothing itself, greatly improves the accuracy of the clothing image recognition, and better than the traditional deep residual network based methods.","PeriodicalId":210502,"journal":{"name":"2020 8th International Conference on Digital Home (ICDH)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121869195","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
Preview Generation for Mathematical Interactive Educational Resources in Netpad Netpad数学互动教育资源的预览生成
2020 8th International Conference on Digital Home (ICDH) Pub Date : 2020-09-01 DOI: 10.1109/ICDH51081.2020.00045
Jianxiong Wang, Linfu Xie, Xiaohong Shi, Xiangping Chen, Xiaoxia Li, Yongsheng Rao
{"title":"Preview Generation for Mathematical Interactive Educational Resources in Netpad","authors":"Jianxiong Wang, Linfu Xie, Xiaohong Shi, Xiangping Chen, Xiaoxia Li, Yongsheng Rao","doi":"10.1109/ICDH51081.2020.00045","DOIUrl":"https://doi.org/10.1109/ICDH51081.2020.00045","url":null,"abstract":"With the development of network technology, some online educational resource platforms have emerged, and the number of resources on these platforms is increasing. How to preview resources is becoming increasingly crucial for users to understand the content of resources and retrieve resources efficiently. NetPad is a dynamic geometric resource platform, the resources on the platform have distinctive characteristics. We need to interact with it to understand the content of interactive dynamic resources, but the cost of performing this manual interactive process is relatively high. In this paper, we propose a method for generating picture preview of mathematical interactive educational resources. Firstly, we analyze the JSON file that stores interactive resource information, obtain interactive element information, and generate an operation sequence. Secondly, we execute the operation sequence using script software to simulate the interaction process between the user and the resource, and save the screenshots in the process to generate picture preview of interactive educational resources. Experimental results indicate that the method can effectively simulate the interactive process, and the generated picture preview is of great help to the user to understand the content of interactive educational resources.","PeriodicalId":210502,"journal":{"name":"2020 8th International Conference on Digital Home (ICDH)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126779461","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
Professional Jurisdiction Recognition for Cross-Domain Filing Based on Deep Hybrid Model 基于深度混合模型的跨域归档专业管辖权识别
2020 8th International Conference on Digital Home (ICDH) Pub Date : 2020-09-01 DOI: 10.1109/ICDH51081.2020.00044
Zhikui Chen, Chaojie Li, Xu Yuan, Fangming Zhong, Xuelai Zhang, Yong Cui
{"title":"Professional Jurisdiction Recognition for Cross-Domain Filing Based on Deep Hybrid Model","authors":"Zhikui Chen, Chaojie Li, Xu Yuan, Fangming Zhong, Xuelai Zhang, Yong Cui","doi":"10.1109/ICDH51081.2020.00044","DOIUrl":"https://doi.org/10.1109/ICDH51081.2020.00044","url":null,"abstract":"This paper proposes a professional jurisdiction recognition algorithm for case materials in cross-domain filing based on a deep hybrid model. Through the parallel combination of CNN and RNN, the spatial and sequence features of text data can be captured without interfering with each other. In addition, we use the tensor outer product to construct them into a high-order data block with rich information and stronger representation capabilities. Extensive experiments are conducted on a new data set with labeled examples consisting of 2068 case materials from three professional courts and one ordinary courts, and the results demonstrate that the proposed model is effective in professional jurisdiction recognition for cross-domain filing.","PeriodicalId":210502,"journal":{"name":"2020 8th International Conference on Digital Home (ICDH)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129135435","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
Optimization of pedestrian navigation algorithm based on reference points of narrow corridor 基于窄小通道参考点的行人导航算法优化
2020 8th International Conference on Digital Home (ICDH) Pub Date : 2020-09-01 DOI: 10.1109/ICDH51081.2020.00043
Hucheng Wang, Xiao-peng Luo, Yifan Huang, Zhi Wang, Ji Li
{"title":"Optimization of pedestrian navigation algorithm based on reference points of narrow corridor","authors":"Hucheng Wang, Xiao-peng Luo, Yifan Huang, Zhi Wang, Ji Li","doi":"10.1109/ICDH51081.2020.00043","DOIUrl":"https://doi.org/10.1109/ICDH51081.2020.00043","url":null,"abstract":"Indoor location services have developed rapidly in recent years, and various scenarios have corresponding positioning methods. We provide a measurement method of the reference positioning according to different molecular blocks based on the analysis of the location in the narrow corridor environment. Through the change of Time Difference of Arrival (TDOA), the location of the user in the different blocks is determined. The proposed algorithm takes effect when the user passes through a block to another block, the coordinates are adjusted to the block boundary position, and the sensor data is reset. The experimental results show that the proposed method can achieve submeter-level positioning accuracy with the lowest resource consumption in a narrow environment or corridor.","PeriodicalId":210502,"journal":{"name":"2020 8th International Conference on Digital Home (ICDH)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125599782","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
Automatic Generation of Informative Video Thumbnail 自动生成信息视频缩略图
2020 8th International Conference on Digital Home (ICDH) Pub Date : 2020-09-01 DOI: 10.1109/ICDH51081.2020.00050
Baoquan Zhao, Hanhui Li, Ruomei Wang, Xiaonan Luo
{"title":"Automatic Generation of Informative Video Thumbnail","authors":"Baoquan Zhao, Hanhui Li, Ruomei Wang, Xiaonan Luo","doi":"10.1109/ICDH51081.2020.00050","DOIUrl":"https://doi.org/10.1109/ICDH51081.2020.00050","url":null,"abstract":"Thumbnail plays a vital role in boosting the discovery and viewership of online video. Although it can be easily obtained by simply selecting a certain image from the video sequence, most of popular videos in today’s video sharing platforms come with elaborately designed custom thumbnails to better showcase the highlight within the video. Unfortunately, both the selection of salient content from thousands of frames and the creation of an eye-catching thumbnail are very time-consuming and require highly specialized skills. In this paper, we present a fully automatic approach for generating informative and eye-catching video thumbnails. The proposed pipeline first splits up a given video into shot units and then selects a set of keyframes using keyframe representativeness and quality assessment metric. After performing salient region detection, a synthetic thumbnail can be obtained by embedding as many as salient regions of keyframes into the carrier image. Experimental results demonstrate the feasibility and effectiveness of our method in informative thumbnail creation.","PeriodicalId":210502,"journal":{"name":"2020 8th International Conference on Digital Home (ICDH)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123956135","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: 3
Fast Spatio-Temporal Multi-Branch Fusion Network for Video Deraining 用于视频训练的快速时空多分支融合网络
2020 8th International Conference on Digital Home (ICDH) Pub Date : 2020-09-01 DOI: 10.1109/ICDH51081.2020.00051
Wei Zhong, Xuefeng Zhang, Long Ma
{"title":"Fast Spatio-Temporal Multi-Branch Fusion Network for Video Deraining","authors":"Wei Zhong, Xuefeng Zhang, Long Ma","doi":"10.1109/ICDH51081.2020.00051","DOIUrl":"https://doi.org/10.1109/ICDH51081.2020.00051","url":null,"abstract":"High-quality videos are essential for outdoor vision systems. Rain is one of the most familiar factors for degrading video quality. Existing works tend to design the complex network architectures with lots of parameters. Unfortunately, they always generate the nonideal results with residual rain streaks and insufficient details, although the network parameters are ample. To handle these issues, we develop a fast Spatio-Temporal Multi-Branch Fusion Network (STMBFN) for effectively handling video deraining. To be concrete, we design a temporal information generation module to align different frames. Different from existing works to directly concatenate these aligned frames, we divide these frames to ensure the closest relationship between the current and other frames. In this way, we can weaken the burden of the network. As a result, we design a multi-branch fusion network based on three three-layers basic networks. In the experimental part, we present sufficient analyses in terms of our STMBFN to illustrate the effectiveness. Further, plenty of experiments are conducted to fully verify our superiority against existing state-of-the-art approaches.","PeriodicalId":210502,"journal":{"name":"2020 8th International Conference on Digital Home (ICDH)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122159291","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: 1
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