2018 IEEE International Conference on Progress in Informatics and Computing (PIC)最新文献

An Anti-occlusion Correlation Filtering Tracking Algorithm for UAV 一种无人机抗遮挡相关滤波跟踪算法

2018 IEEE International Conference on Progress in Informatics and Computing (PIC) Pub Date : 2018-12-01 DOI: 10.1109/PIC.2018.8706132

Zun Xu, Yan Ding, Jiayuan Shan, Xiaoxiao Xie

{"title":"An Anti-occlusion Correlation Filtering Tracking Algorithm for UAV","authors":"Zun Xu, Yan Ding, Jiayuan Shan, Xiaoxiao Xie","doi":"10.1109/PIC.2018.8706132","DOIUrl":"https://doi.org/10.1109/PIC.2018.8706132","url":null,"abstract":"In the scenario of Unmanned Aerial Vehicle (UAV), the angle and the height at which the UAV observes the object cause partial occlusion, deformation, and size changing of object image. Based on the Discriminative Correlation Filter (DCF) algorithm, this paper proposes a new tracking algorithm DCF-GA (Discriminative Correlation Filter with Generation of Adversarial example) to achieve anti-occlusion in the scenario of UAV. Firstly, we design a mask selection strategy to generate the adversarial example with occlusion, which can enhance the antiocclusion performance of our algorithm. The response losses of DCF reveal the impacts of adversaries so that they are used to select an appropriate mask. And then, we provide an optimization scheme of object feature selection based on the singular values extracted from histogram of oriented gradient (HOG) feature and convolutional neural network (CNN) feature respectively. Moreover, to overcome the scale changes of the object image, a multidimensional templates set is proposed and the best one is determined by the maximum of their DCF responses. Finally, we add the background patches around the region of interest (ROI) into the sample set to suppress the background clutter. The tracking algorithm we proposed in this paper is compared with some other algorithms in both the UAV video sequence and the OTB dataset. The experimental results show that our DCF-GA algorithm is effective when the object is partially occluded and when the size of object image changes.","PeriodicalId":236106,"journal":{"name":"2018 IEEE International Conference on Progress in Informatics and Computing (PIC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124863997","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

Structure Connectivity and Substructure Connectivity of Alternating Group Graphs 交替群图的结构连通性和子结构连通性

2018 IEEE International Conference on Progress in Informatics and Computing (PIC) Pub Date : 2018-12-01 DOI: 10.1109/PIC.2018.8706296

Lantao You, Yuejuan Han, Xi Wang, Chen Zhou, Rui Gu, Chen Lu

引用次数: 5

Research of Dynamic Load Identification for Rock Roadheader 岩石掘进机动载荷识别研究

2018 IEEE International Conference on Progress in Informatics and Computing (PIC) Pub Date : 2018-12-01 DOI: 10.1109/PIC.2018.8706319

Hongjie Shi, Xiangmin Dong, N. Zhang, Ning Ding

引用次数: 3

A Prediction Based Server Cluster Capacity Planning Strategy 基于预测的服务器集群容量规划策略

2018 IEEE International Conference on Progress in Informatics and Computing (PIC) Pub Date : 2018-12-01 DOI: 10.1109/PIC.2018.8706273

Xiaofu Huang, Jian Cao, Yudong Tan

{"title":"A Prediction Based Server Cluster Capacity Planning Strategy","authors":"Xiaofu Huang, Jian Cao, Yudong Tan","doi":"10.1109/PIC.2018.8706273","DOIUrl":"https://doi.org/10.1109/PIC.2018.8706273","url":null,"abstract":"Cloud computing is an Internet-based service which provides shared virtual resource and data to accomplish certain computation. In order for the servers to have sufficient resources when the request arrives, as well as save server resources as much as possible, we propose a prediction-based server capacity planning and dynamic scheduling algorithm. There are mainly three steps in our capacity planning algorithm. The first step characterizes the given data on several indices and then present an effective model in order to predict the oncoming demands in the near future. The second step generates the workload of servers combined with the predicted demands and then make capacity planning based on this workload. Thus it's obvious that the effectiveness of capacity planning depends on the accuracy of prediction to a great extent. Finally, a demand prediction based strategy on workload allocation is brought out. A dynamic resource allocation strategy is given to ensure the quality of service at any moment in future meanwhile taking energy consumption into consideration. The results of the experiment show that the required server number decreases by 33% after the prediction-based capacity planning applying on server scheduling.","PeriodicalId":236106,"journal":{"name":"2018 IEEE International Conference on Progress in Informatics and Computing (PIC)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129585536","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: 2

A Fast Visualization Method of Radiation Field Based on Target’s Geometric Feature 基于目标几何特征的辐射场快速可视化方法

2018 IEEE International Conference on Progress in Informatics and Computing (PIC) Pub Date : 2018-12-01 DOI: 10.1109/PIC.2018.8706136

Junling Qin, D. Ren, Weiqing Li

{"title":"A Fast Visualization Method of Radiation Field Based on Target’s Geometric Feature","authors":"Junling Qin, D. Ren, Weiqing Li","doi":"10.1109/PIC.2018.8706136","DOIUrl":"https://doi.org/10.1109/PIC.2018.8706136","url":null,"abstract":"In the simulation of complex model’s radiation field, we usually use finite element mesh for visualization. However, finite element cannot represent target’s geometric feature accurately. In addition, huge number of patches will seriously affect rendering speed in real-time simulation. In this paper, we propose a method to map finite element mesh to geometric model surfaces, replacing the drawing of a dense finite element mesh with a geometric model drawing. The method mainly consists of four parts. First, the mapping between feature points and the texture is established by the non-parametric surface mapping skill. Second, based on the correspondence relation between feature points and the texture, the mapping between points on the geometric model surfaces to the finite element mesh is completed. Third, within the texture, bilinear interpolation is applied to get radiation field values of all the texture pixels. Finally, the texture, which represents radiation values of the target, is stored in form of PNG picture. This paper defines a texture for each part of the geometric model to represent radiation values. The drawing of geometric model is much faster than that of finite element mesh because the patches are reduced greatly. The simulation results show that this method can realize accurate and quick visualization of the target’s radiation field.","PeriodicalId":236106,"journal":{"name":"2018 IEEE International Conference on Progress in Informatics and Computing (PIC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129303580","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 3-Layer Structural Analysis Framework for Chinese Text Understanding 面向中文文本理解的三层结构分析框架

2018 IEEE International Conference on Progress in Informatics and Computing (PIC) Pub Date : 2018-12-01 DOI: 10.1109/PIC.2018.8706323

Siyuan Shen, Hao Lian, Jia Liu, Tieke He

引用次数: 0

(Strong) Rainbow Connection Number of Line, Middle and Total Graph of Sunlet Graph (强)太阳图的线、中图和总图的彩虹连接数

2018 IEEE International Conference on Progress in Informatics and Computing (PIC) Pub Date : 2018-12-01 DOI: 10.1109/PIC.2018.8706299

Yan Zhao, Shasha Li, Sujuan Liu

引用次数: 2

Face Image Quality Quantitative Assessment for Forensic Identification of Human Images 人脸图像质量定量评估用于人体图像的法医鉴定

2018 IEEE International Conference on Progress in Informatics and Computing (PIC) Pub Date : 2018-12-01 DOI: 10.1109/pic.2018.8706327

Jinhua Zeng, Huaping Zhu, Shaopei Shi, Xiulian Qiu

{"title":"Face Image Quality Quantitative Assessment for Forensic Identification of Human Images","authors":"Jinhua Zeng, Huaping Zhu, Shaopei Shi, Xiulian Qiu","doi":"10.1109/pic.2018.8706327","DOIUrl":"https://doi.org/10.1109/pic.2018.8706327","url":null,"abstract":"With the development of the face recognition technology, the face recognition techniques are more and more applied in the scenario of the forensic science. Forensic identification of human images is a forensic activity for verifying whether the questioned and the known face images are the same ones. The one to one face verification technique can be well applied in the above application. Researching on the effect of face image quality on the performance of face verification systems in the application of the forensic identification of human images leads to the problem of face image quality assessment. Firstly, we discuss and analyze factors that affect the assessment of face image quality in forensic identification of human images. The factors consist of the age, expression, imaging angle, image quality and others, which will influence the performance of the face verification system. Then we propose a quantitative analysis method for the assessment of face image quality, which is relied on the verification performance of face verification systems. The effect of face images under specific conditions is studied. The face image quality under the specific factor condition is quantitatively scored according to the similarity quantification value between face images calculated by the face verification system. For the implement of the face verification system, the deep learning based face recognition method is used for objective evaluation of the face image quality. The results in the paper have shown the important significance of our proposed method for the objective evaluation of face image quality, and for the reasonable selection of face images in videos in the practical cases of the forensic identification of human images.","PeriodicalId":236106,"journal":{"name":"2018 IEEE International Conference on Progress in Informatics and Computing (PIC)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125610055","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

Research Progress of Security Protection for Dispatching Automation System 调度自动化系统安全防护研究进展

2018 IEEE International Conference on Progress in Informatics and Computing (PIC) Pub Date : 2018-12-01 DOI: 10.1109/PIC.2018.8706298

Yunshan Tang, Nibin Zou, Yangyang Shi, X. Wang

引用次数: 0

A Traffic Flow Prediction Approach: LSTM with Detrending 一种交通流预测方法:具有去趋势的LSTM

2018 IEEE International Conference on Progress in Informatics and Computing (PIC) Pub Date : 2018-12-01 DOI: 10.1109/PIC.2018.8706313

Zheng Zhao, Yaying Zhang

引用次数: 5