2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)最新文献
Pub Date : 2019-10-01DOI: 10.1109/iucc/dsci/smartcns.2019.00023
{"title":"IUCC 2019 Organizing Committee","authors":"","doi":"10.1109/iucc/dsci/smartcns.2019.00023","DOIUrl":"https://doi.org/10.1109/iucc/dsci/smartcns.2019.00023","url":null,"abstract":"","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123625873","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}
Pub Date : 2019-10-01DOI: 10.1109/IUCC/DSCI/SmartCNS.2019.00124
Zhijun Xu, Yichen Liu, Jun Zhang, Z. Song, Jun Li, Jihua Zhou
Nowadays the composition and structure of the manufacturing industry supply chain have become increasingly complex. The loss and not-in-time transmission of the supply chain information have aggravated the bullwhip effect. At the same time, due to the lack of reliable information storage, the difficulties of traceability and accountability have also caused supply chain management to fall into the bottleneck. The blockchain has the characteristics of supporting distributed networking, information synchronization among nodes, digital encryption, traceable information and block content that cannot be tampered, which is suitable for use in supply chain, and can provide solution for it. In this paper, a design scheme of integrated platform for information service provided by participants in supply chain and based on Ethereum blockchain is proposed. By using Ethereum smart contracts, the common business involved in the supply chain is realized using blockchain technology, and the key information of supply chain production and circulation is stored on the blockchain to ensure the information cannot be tampered. At the same time, a reputation evaluating method based on smart contracts is used to evaluate the reputation of enterprises in supply chain, which can provide reference for supplier selection among enterprises.
{"title":"Manufacturing Industry Supply Chain Management Based on the Ethereum Blockchain","authors":"Zhijun Xu, Yichen Liu, Jun Zhang, Z. Song, Jun Li, Jihua Zhou","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00124","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00124","url":null,"abstract":"Nowadays the composition and structure of the manufacturing industry supply chain have become increasingly complex. The loss and not-in-time transmission of the supply chain information have aggravated the bullwhip effect. At the same time, due to the lack of reliable information storage, the difficulties of traceability and accountability have also caused supply chain management to fall into the bottleneck. The blockchain has the characteristics of supporting distributed networking, information synchronization among nodes, digital encryption, traceable information and block content that cannot be tampered, which is suitable for use in supply chain, and can provide solution for it. In this paper, a design scheme of integrated platform for information service provided by participants in supply chain and based on Ethereum blockchain is proposed. By using Ethereum smart contracts, the common business involved in the supply chain is realized using blockchain technology, and the key information of supply chain production and circulation is stored on the blockchain to ensure the information cannot be tampered. At the same time, a reputation evaluating method based on smart contracts is used to evaluate the reputation of enterprises in supply chain, which can provide reference for supplier selection among enterprises.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125888473","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}
Pub Date : 2019-10-01DOI: 10.1109/IUCC/DSCI/SmartCNS.2019.00127
Jian Guan, Lexi Xu, Tao Zhang, Jie Gao, Xinzhou Cheng
The existing evaluation methods of wireless network cross-boundary coverage are either uneconomical or poorly effective. Based on location data of APP sampling points from smart terminals, a novel evaluation method is proposed which can accurately and quickly locate cross-boundary coverage issues of base stations. On one hand, using location data comes from GPS positioning data of user terminals, its error is smaller than using from the network. On the other hand, APP data collected from massive users in the existing network covers complex and diverse scenarios, making the evaluation applicable, reliable, accurate, and economical.
{"title":"Research on Evaluation Method of Wireless Network Cross-Boundary Coverage Based on Smart Terminals Location Data","authors":"Jian Guan, Lexi Xu, Tao Zhang, Jie Gao, Xinzhou Cheng","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00127","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00127","url":null,"abstract":"The existing evaluation methods of wireless network cross-boundary coverage are either uneconomical or poorly effective. Based on location data of APP sampling points from smart terminals, a novel evaluation method is proposed which can accurately and quickly locate cross-boundary coverage issues of base stations. On one hand, using location data comes from GPS positioning data of user terminals, its error is smaller than using from the network. On the other hand, APP data collected from massive users in the existing network covers complex and diverse scenarios, making the evaluation applicable, reliable, accurate, and economical.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127099450","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}
Pub Date : 2019-10-01DOI: 10.1109/IUCC/DSCI/SmartCNS.2019.00117
Yajie Wang, Yuan Huang
A path planning algorithm is proposed for the problems of high node randomness and repeatability using the Rapidly-exploring Random Tree (RRT) algorithm in the path planning. Firstly, the method of region division centered on newly generated nodes is proposed to reduce randomness, the generation rules of temporary target nodes are guided to reduce repetitiveness, then improve the efficiency of path planning through adaptive step size strategy, smooth the planned path to improve the length of the path in the end. Simulation results show that the improved RRT algorithm can effectively plan the path for mobile robots.
{"title":"Mobile Robot Path Planning Algorithm Based on Rapidly-Exploring Random Tree","authors":"Yajie Wang, Yuan Huang","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00117","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00117","url":null,"abstract":"A path planning algorithm is proposed for the problems of high node randomness and repeatability using the Rapidly-exploring Random Tree (RRT) algorithm in the path planning. Firstly, the method of region division centered on newly generated nodes is proposed to reduce randomness, the generation rules of temporary target nodes are guided to reduce repetitiveness, then improve the efficiency of path planning through adaptive step size strategy, smooth the planned path to improve the length of the path in the end. Simulation results show that the improved RRT algorithm can effectively plan the path for mobile robots.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129974448","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}
Pub Date : 2019-10-01DOI: 10.1109/IUCC/DSCI/SmartCNS.2019.00088
Wei Zhang, Yi Wang, Hao Chen, Xia Wei
The collaborative filtering recommendation algorithm based on k-means clustering is more accurate in the case of large amount of users' ratings, and it is not suitable for the situations that users' ratings are relatively small. The video gene recommendation algorithm based on linear regression uses the opposite scenario. In order to solve the problem of general application of the single recommendation algorithm, this paper proposes a hybrid recommendation algorithm based on collaborative filtering and video gene. This algorithm first constructs user project matrix, calculates user similarity, and then cluster to get a recommendation list by k-means clustering. Then the genetic structure of the video is analysed, the gene preference is combined by style preference and regional preference, and the weight of the gene is determined by linear regression, at last, a recommendation list is obtained by selecting the object with high gene preference. Finally, the final recommendation results are obtained by weighting the recommended results in two recommendation lists. The experimental results show that the proposed algorithm has higher accuracy no matter when the number of users' ratings is large or small.
{"title":"An Efficient Personalized Video Recommendation Algorithm Based on Mixed Mode","authors":"Wei Zhang, Yi Wang, Hao Chen, Xia Wei","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00088","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00088","url":null,"abstract":"The collaborative filtering recommendation algorithm based on k-means clustering is more accurate in the case of large amount of users' ratings, and it is not suitable for the situations that users' ratings are relatively small. The video gene recommendation algorithm based on linear regression uses the opposite scenario. In order to solve the problem of general application of the single recommendation algorithm, this paper proposes a hybrid recommendation algorithm based on collaborative filtering and video gene. This algorithm first constructs user project matrix, calculates user similarity, and then cluster to get a recommendation list by k-means clustering. Then the genetic structure of the video is analysed, the gene preference is combined by style preference and regional preference, and the weight of the gene is determined by linear regression, at last, a recommendation list is obtained by selecting the object with high gene preference. Finally, the final recommendation results are obtained by weighting the recommended results in two recommendation lists. The experimental results show that the proposed algorithm has higher accuracy no matter when the number of users' ratings is large or small.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126303494","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}
Pub Date : 2019-10-01DOI: 10.1109/IUCC/DSCI/SmartCNS.2019.00044
Yupeng Wang, Junyan Kang, Lening Wang
In Heterogeneous Networks (HetNets), User Equipments(UEs) in pico cells may suffer from significant co-channel interference from macro stations. The 3rd Generation Partnership Project (3GPP) organization has proposed the concept of Almost Blank Subframe (ABS) so as to reduce the interference of macro stations to pico UEs. Addressing the problem that the introduction of ABS makes it impossible for pico UEs to correctly obtain channel conditions on different subframes, this paper proposes an efficient scheme based on a variable parameter Lambda report and Lambda estimation to derive Channel Quality Indicator (CQI). The method is applicable to the ABS and non-Almost Blank Subframe (non-ABS). It compensates the non-restricted measured CQI with different offsets, based on ABS density and ratio of interference levels from macro cells and pico cells to obtain CQI on different subframes. Simulation and analytical results show that our proposed scheme can achieve approximately 59% gain over the 3GPP system and reduce report overhead significantly without inducing penalties on throughput.
{"title":"Efficient CQI Estimation for Synchronized ABS Configuration in HetNet","authors":"Yupeng Wang, Junyan Kang, Lening Wang","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00044","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00044","url":null,"abstract":"In Heterogeneous Networks (HetNets), User Equipments(UEs) in pico cells may suffer from significant co-channel interference from macro stations. The 3rd Generation Partnership Project (3GPP) organization has proposed the concept of Almost Blank Subframe (ABS) so as to reduce the interference of macro stations to pico UEs. Addressing the problem that the introduction of ABS makes it impossible for pico UEs to correctly obtain channel conditions on different subframes, this paper proposes an efficient scheme based on a variable parameter Lambda report and Lambda estimation to derive Channel Quality Indicator (CQI). The method is applicable to the ABS and non-Almost Blank Subframe (non-ABS). It compensates the non-restricted measured CQI with different offsets, based on ABS density and ratio of interference levels from macro cells and pico cells to obtain CQI on different subframes. Simulation and analytical results show that our proposed scheme can achieve approximately 59% gain over the 3GPP system and reduce report overhead significantly without inducing penalties on throughput.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"197 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127595144","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}
Pub Date : 2019-10-01DOI: 10.1109/IUCC/DSCI/SmartCNS.2019.00033
Ye Hu, Liang Zhao, Xin Zhou
In order to meet the requirement of rapid process preparation for new aircraft in heat and surface treatment, a method of batch acquisition of model data is proposed based on the principle of centralized batch production in heat and surface treatment workshop. The batch acquisition of MBD information, surface area, and preview are realized with the secondary development of CATIA/CAA, which provides a fast and accurate method for extracting the information needed by heat and surface process. This method improves the quality and efficiency of heat and surface treatment process and is of some practical value in aircraft manufacturing.
{"title":"A Batch Acquisition of Model Data for Aircraft Heat and Surface Treatment","authors":"Ye Hu, Liang Zhao, Xin Zhou","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00033","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00033","url":null,"abstract":"In order to meet the requirement of rapid process preparation for new aircraft in heat and surface treatment, a method of batch acquisition of model data is proposed based on the principle of centralized batch production in heat and surface treatment workshop. The batch acquisition of MBD information, surface area, and preview are realized with the secondary development of CATIA/CAA, which provides a fast and accurate method for extracting the information needed by heat and surface process. This method improves the quality and efficiency of heat and surface treatment process and is of some practical value in aircraft manufacturing.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117160393","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}
Pub Date : 2019-10-01DOI: 10.1109/IUCC/DSCI/SmartCNS.2019.00133
Chang-an Ren, Yinzhen Huang, Qingyun Luo, Xiaocui Li
In order to improve the utilization ratio of virtual machine resource, and then realize reasonable scheduling of it. In this paper, we propose a novel cloud computing resource scheduling optimization approach based on firefly algorithm. Firstly, mathematical model is built according to virtual machine resource scheduling problem. Then, considering the optimal time span and load function, we propose improved firefly algorithm, named selective elimination and decision domain strategy of firefly algorithm (SDFA) and use the SDFA to search the optimal scheme. Finally, we use the CloudSim platform to evaluate the effectiveness of our proposed approach. Experimental results show that our proposed approach can obtain good scheduling scheme to ensure load balance of virtual machine resource, which can meet the user's preferences.
{"title":"Resource Scheduling in Cloud Computing Based on Firefly Algorithm","authors":"Chang-an Ren, Yinzhen Huang, Qingyun Luo, Xiaocui Li","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00133","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00133","url":null,"abstract":"In order to improve the utilization ratio of virtual machine resource, and then realize reasonable scheduling of it. In this paper, we propose a novel cloud computing resource scheduling optimization approach based on firefly algorithm. Firstly, mathematical model is built according to virtual machine resource scheduling problem. Then, considering the optimal time span and load function, we propose improved firefly algorithm, named selective elimination and decision domain strategy of firefly algorithm (SDFA) and use the SDFA to search the optimal scheme. Finally, we use the CloudSim platform to evaluate the effectiveness of our proposed approach. Experimental results show that our proposed approach can obtain good scheduling scheme to ensure load balance of virtual machine resource, which can meet the user's preferences.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121017625","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}
Pub Date : 2019-10-01DOI: 10.1109/IUCC/DSCI/SmartCNS.2019.00100
Xingbo Gao, Chao Che, Lasheng Zhao, Jianxin Zhang
In recent years, more and more patent lawsuits have been filed by Chinese enterprises, represented by the "Section 337 investigations" of the United States. In order to help Chinese enterprises cope with the challenges of patent litigation, a matrix factorization based recommendation system are used to predict the legal risk of 337 investigation. However, the results predicted by the model are prone to over-fitting. In order to solve this problem, this paper proposes a new recommendation framework, namely elastic time predictor. The model is a hybrid model combining matrix factorization and truncation function. We encode the information of the prosecution case of major companies and decompose it into two sub-matrices, and then combine the decomposed matrix with the segmentation of the truncation function to maintain the entire recommended frame flexible. In the recommended approach, we consider the risk of litigation that a company may experience when entering a new market, for example the risk that a potential competitor will file a lawsuit against a new entrant. We use actual data to conduct experiments, and the experimental results show that the proposed method is superior to the baseline method and has significant advantages.
{"title":"Predicting the Legal Risk of \"Section 337 Investigations\" by Elastic Time Predictor","authors":"Xingbo Gao, Chao Che, Lasheng Zhao, Jianxin Zhang","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00100","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00100","url":null,"abstract":"In recent years, more and more patent lawsuits have been filed by Chinese enterprises, represented by the \"Section 337 investigations\" of the United States. In order to help Chinese enterprises cope with the challenges of patent litigation, a matrix factorization based recommendation system are used to predict the legal risk of 337 investigation. However, the results predicted by the model are prone to over-fitting. In order to solve this problem, this paper proposes a new recommendation framework, namely elastic time predictor. The model is a hybrid model combining matrix factorization and truncation function. We encode the information of the prosecution case of major companies and decompose it into two sub-matrices, and then combine the decomposed matrix with the segmentation of the truncation function to maintain the entire recommended frame flexible. In the recommended approach, we consider the risk of litigation that a company may experience when entering a new market, for example the risk that a potential competitor will file a lawsuit against a new entrant. We use actual data to conduct experiments, and the experimental results show that the proposed method is superior to the baseline method and has significant advantages.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121092938","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}
Pub Date : 2019-10-01DOI: 10.1109/IUCC/DSCI/SmartCNS.2019.00159
C. Ndubuisi, Hua Li
Microsoft Kinect sensor has been used for all sort of computer vision projects since inception, as it provides us with both RGB and depth data. With a high range of depth information provided by the Microsoft Kinect v2 Infrared (IR) depth sensors, there has been increased attention in utilizing this depth information for detection and tracking. In this paper, we proposed a Single-pixel-grid based method for calculating the pixel of an object that is the closest or highest within a particular threshold. After establishing the record holding pixel object, we developed an algorithm for detecting and tracking the location of the object based on the pixel. At the end of the experiment, results show that using this algorithm, the Kinect v2 was able to detect the pixel that is the closest or highest in two tested thresholds and as well tracked accurately the object with the record pixel point. Analysis and comparison of results shows improved accuracy in object location detection using our algorithm.
{"title":"Single-Pixel Estimation for Enhanced Object Detection and Recognition with Kinect for Windows V2","authors":"C. Ndubuisi, Hua Li","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00159","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00159","url":null,"abstract":"Microsoft Kinect sensor has been used for all sort of computer vision projects since inception, as it provides us with both RGB and depth data. With a high range of depth information provided by the Microsoft Kinect v2 Infrared (IR) depth sensors, there has been increased attention in utilizing this depth information for detection and tracking. In this paper, we proposed a Single-pixel-grid based method for calculating the pixel of an object that is the closest or highest within a particular threshold. After establishing the record holding pixel object, we developed an algorithm for detecting and tracking the location of the object based on the pixel. At the end of the experiment, results show that using this algorithm, the Kinect v2 was able to detect the pixel that is the closest or highest in two tested thresholds and as well tracked accurately the object with the record pixel point. Analysis and comparison of results shows improved accuracy in object location detection using our algorithm.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115493916","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}
2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)
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