Pub Date : 2020-12-11DOI: 10.1109/ICCC51575.2020.9345004
Feng Qian
With the rapid development of cities, massive and complex traffic data is being generated and collected. The traffic data is not intuitive and cannot highlight key information about urban traffic conditions. However, traffic data visualization can directly correlate users with the data, and support users to interact with data in a convenient and visual way. Then realize the feedback of blending user wisdom and machine intelligence. This paper investigates a structured survey of the state of the art in the visualization of traffic data. First, we reviewed five representative traffic data visualization methods including WebVRGIS based traffic analysis and visualization system, TripMiner, IoV distributed architecture, SMASH architecture, and LDA-based topic modelling. Meanwhile, we analyzed the traffic datasets that applied in each method. Then we summarize these methods from seven aspects: scalability, data storage, data update, interactivity, reliability, data anomaly detection, and spatiotemporal visualization. In addition, we make a detailed comparative analysis of the key capabilities of five representative traffic data visualization methods in processing traffic big data. Finally, we conclude that the SMASH architecture performs better in processing high speed and large flow traffic data. Moreover, we propose a novel direction for optimizing traffic data visualization techniques.
{"title":"Visualization of Traffic Data: A Survey of Methods and Datasets","authors":"Feng Qian","doi":"10.1109/ICCC51575.2020.9345004","DOIUrl":"https://doi.org/10.1109/ICCC51575.2020.9345004","url":null,"abstract":"With the rapid development of cities, massive and complex traffic data is being generated and collected. The traffic data is not intuitive and cannot highlight key information about urban traffic conditions. However, traffic data visualization can directly correlate users with the data, and support users to interact with data in a convenient and visual way. Then realize the feedback of blending user wisdom and machine intelligence. This paper investigates a structured survey of the state of the art in the visualization of traffic data. First, we reviewed five representative traffic data visualization methods including WebVRGIS based traffic analysis and visualization system, TripMiner, IoV distributed architecture, SMASH architecture, and LDA-based topic modelling. Meanwhile, we analyzed the traffic datasets that applied in each method. Then we summarize these methods from seven aspects: scalability, data storage, data update, interactivity, reliability, data anomaly detection, and spatiotemporal visualization. In addition, we make a detailed comparative analysis of the key capabilities of five representative traffic data visualization methods in processing traffic big data. Finally, we conclude that the SMASH architecture performs better in processing high speed and large flow traffic data. Moreover, we propose a novel direction for optimizing traffic data visualization techniques.","PeriodicalId":386048,"journal":{"name":"2020 IEEE 6th International Conference on Computer and Communications (ICCC)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124547558","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 : 2020-12-11DOI: 10.1109/ICCC51575.2020.9345043
Haixing Li, Haibo Luo
In medical images, the observer's manual description of different structures is very different, and it spans a wide range of various structures and pathologies. This variability (which is a characteristic of biological issues, imaging modality and expert annotators) has not been fully considered in the design of computer algorithms for medical image quantification. So far, few people predict the uncertainty of medical image segmentation. In this paper, we designed a V-shaped network to quantify the uncertainty in prostate MRI image segmentation. We have embedded a feature pyramid attention module in the backbone network, which can extract high-level semantic context information at different scales and provide a pixel-level attention to the decoder. At the same time, the module will not bring a large computational burden. In our experiments, we tested the performance of the proposed method on 55 clinical subjects.
{"title":"Uncertainty Quantification in Medical Image Segmentation","authors":"Haixing Li, Haibo Luo","doi":"10.1109/ICCC51575.2020.9345043","DOIUrl":"https://doi.org/10.1109/ICCC51575.2020.9345043","url":null,"abstract":"In medical images, the observer's manual description of different structures is very different, and it spans a wide range of various structures and pathologies. This variability (which is a characteristic of biological issues, imaging modality and expert annotators) has not been fully considered in the design of computer algorithms for medical image quantification. So far, few people predict the uncertainty of medical image segmentation. In this paper, we designed a V-shaped network to quantify the uncertainty in prostate MRI image segmentation. We have embedded a feature pyramid attention module in the backbone network, which can extract high-level semantic context information at different scales and provide a pixel-level attention to the decoder. At the same time, the module will not bring a large computational burden. In our experiments, we tested the performance of the proposed method on 55 clinical subjects.","PeriodicalId":386048,"journal":{"name":"2020 IEEE 6th International Conference on Computer and Communications (ICCC)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129541555","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 : 2020-12-11DOI: 10.1109/ICCC51575.2020.9345119
Haibo Zhang, Changhua Yao, Lei Zhu, Lei Wang, Fanpeng Zhu, Yiming Chen
The communication relationship can reflect the hidden information of the communication network, which is of great significance for discovering important nodes in the network. To overcome the difficulty of manually extracting expert features, this paper uses deep learning methods to study the communication relationship recognition. First, use the deep learning model to classify the spectrum data directly, and model the communication relationship as a classification problem with time feature data for processing. It is found that the neural network model is easy to fall into a local minimum; in order to limit the impact of the local minimum problem on recognition In this paper, combining the rules of frequency hopping communication to process the data, make the neural network take as few tasks as possible, and then propose the second design scheme, the communication time series classification scheme, and the final recognition rate reaches 97% on the test set. This article uses long and short memory networks and convolutional neural networks to conduct experiments. Among them, the improved VGG network structure has the best recognition rate in communication problems. The factors that affect the recognition rate of neural networks in the identification of communication relationships are discussed in depth, and suggestions on how to adjust these factors are given based on theory and experiment.
{"title":"Recognition of Communication Relationship Based on the Spectrum Monitoring Data by Improved VGGNET","authors":"Haibo Zhang, Changhua Yao, Lei Zhu, Lei Wang, Fanpeng Zhu, Yiming Chen","doi":"10.1109/ICCC51575.2020.9345119","DOIUrl":"https://doi.org/10.1109/ICCC51575.2020.9345119","url":null,"abstract":"The communication relationship can reflect the hidden information of the communication network, which is of great significance for discovering important nodes in the network. To overcome the difficulty of manually extracting expert features, this paper uses deep learning methods to study the communication relationship recognition. First, use the deep learning model to classify the spectrum data directly, and model the communication relationship as a classification problem with time feature data for processing. It is found that the neural network model is easy to fall into a local minimum; in order to limit the impact of the local minimum problem on recognition In this paper, combining the rules of frequency hopping communication to process the data, make the neural network take as few tasks as possible, and then propose the second design scheme, the communication time series classification scheme, and the final recognition rate reaches 97% on the test set. This article uses long and short memory networks and convolutional neural networks to conduct experiments. Among them, the improved VGG network structure has the best recognition rate in communication problems. The factors that affect the recognition rate of neural networks in the identification of communication relationships are discussed in depth, and suggestions on how to adjust these factors are given based on theory and experiment.","PeriodicalId":386048,"journal":{"name":"2020 IEEE 6th International Conference on Computer and Communications (ICCC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130534089","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 : 2020-12-11DOI: 10.1109/ICCC51575.2020.9345191
Sheng-hui Zhao, Wenjiang Wu
To address the time-consuming problem of scheduling the transmission of heterogeneous data across sources in cloud computing, many existing scheduling methods are implemented by heuristic algorithms, which usually cause load imbalance and low throughput and acceleration. Therefore, this paper proposes a cross-source scheduling method for heterogeneous data in a cloud environment, which carries out data prefetching before the actual scheduling, greatly reducing the computation amount during scheduling and thus the scheduling resource overhead. Then, all variables are updated, the quality of the heterogeneous data cross-source sub-stream to be scheduled is arranged, and it is regarded as the weight of the sub-stream data, the best quality sub-stream data among the heterogeneous multi-source sub-stream data is selected in the scheduling window each time for scheduling transmission, and the processing of all data sub-streams on paper is finished. The experimental results show that the method proposed in this paper is capable of cross-source scheduling of heterogeneous data in a cloud environment with high load balancing, throughput and acceleration ratios.
{"title":"A Cross-source Scheduling Method for Heterogeneous Data in Cloud Environment","authors":"Sheng-hui Zhao, Wenjiang Wu","doi":"10.1109/ICCC51575.2020.9345191","DOIUrl":"https://doi.org/10.1109/ICCC51575.2020.9345191","url":null,"abstract":"To address the time-consuming problem of scheduling the transmission of heterogeneous data across sources in cloud computing, many existing scheduling methods are implemented by heuristic algorithms, which usually cause load imbalance and low throughput and acceleration. Therefore, this paper proposes a cross-source scheduling method for heterogeneous data in a cloud environment, which carries out data prefetching before the actual scheduling, greatly reducing the computation amount during scheduling and thus the scheduling resource overhead. Then, all variables are updated, the quality of the heterogeneous data cross-source sub-stream to be scheduled is arranged, and it is regarded as the weight of the sub-stream data, the best quality sub-stream data among the heterogeneous multi-source sub-stream data is selected in the scheduling window each time for scheduling transmission, and the processing of all data sub-streams on paper is finished. The experimental results show that the method proposed in this paper is capable of cross-source scheduling of heterogeneous data in a cloud environment with high load balancing, throughput and acceleration ratios.","PeriodicalId":386048,"journal":{"name":"2020 IEEE 6th International Conference on Computer and Communications (ICCC)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116504684","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 : 2020-12-11DOI: 10.1109/ICCC51575.2020.9345179
Xingyu Zhao, Tian Lin, Tongtong Hui, Yu Zhu
Hybrid analog and digital beamforming (HBF) for large-scale antenna arrays with limited radio frequency chains has been regarded as one of the promising candidates for future wireless communications. Due to the limitation of hardware, this problem becomes more challenging compared with the design of conventional digital beamforming schemes. In this paper, we investigate the HBF design for broadband multiuser millimeter wave multiple-input multiple-output systems. By utilizing the alternating minimization method and taking the weighted sum mean square error minimization criterion, a strictly convergent algorithm based on the manifold optimization method is proposed to efficiently tackle the non-convex problem. The algorithm is applicable to the analog beamforming design in both the fully-connected architecture and the partially-connected architecture. Simulation results demonstrate the fast convergence and excellent performance of the proposed scheme.
{"title":"Hybrid Beamforming for Multiuser Millimeter Wave MIMO-OFDM Systems","authors":"Xingyu Zhao, Tian Lin, Tongtong Hui, Yu Zhu","doi":"10.1109/ICCC51575.2020.9345179","DOIUrl":"https://doi.org/10.1109/ICCC51575.2020.9345179","url":null,"abstract":"Hybrid analog and digital beamforming (HBF) for large-scale antenna arrays with limited radio frequency chains has been regarded as one of the promising candidates for future wireless communications. Due to the limitation of hardware, this problem becomes more challenging compared with the design of conventional digital beamforming schemes. In this paper, we investigate the HBF design for broadband multiuser millimeter wave multiple-input multiple-output systems. By utilizing the alternating minimization method and taking the weighted sum mean square error minimization criterion, a strictly convergent algorithm based on the manifold optimization method is proposed to efficiently tackle the non-convex problem. The algorithm is applicable to the analog beamforming design in both the fully-connected architecture and the partially-connected architecture. Simulation results demonstrate the fast convergence and excellent performance of the proposed scheme.","PeriodicalId":386048,"journal":{"name":"2020 IEEE 6th International Conference on Computer and Communications (ICCC)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121451915","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 : 2020-12-11DOI: 10.1109/ICCC51575.2020.9344981
Wenzhao Zhu, Lei Luo, Jinwei Sun, M. G. Christensen
Noise containing both strong narrowband and broadband components generated by rotating machine occur in many situations where active noise control is desirable. Such noise may be reduced by hybrid active noise control (HANC) methods, as shown in previous work. However, the performance of conventional HANC methods decrease when impulsive interference occurs. To improve the tracking and robustness of such HANC systems, a new hybrid noise control system with anti-pulse variable step size algorithm (APV-HANC) is proposed. By using new variable step size method and HANC structure, the APV-HANC method has better tracking and robustness performance of the whole system when impulsive noise occurs. Theoretical analysis and simulations confirms the superior performance of the proposed method.
{"title":"A New Variable Step Size Algorithm Based Hybrid Active Noise Control System for Gaussian Noise with Impulsive Interference","authors":"Wenzhao Zhu, Lei Luo, Jinwei Sun, M. G. Christensen","doi":"10.1109/ICCC51575.2020.9344981","DOIUrl":"https://doi.org/10.1109/ICCC51575.2020.9344981","url":null,"abstract":"Noise containing both strong narrowband and broadband components generated by rotating machine occur in many situations where active noise control is desirable. Such noise may be reduced by hybrid active noise control (HANC) methods, as shown in previous work. However, the performance of conventional HANC methods decrease when impulsive interference occurs. To improve the tracking and robustness of such HANC systems, a new hybrid noise control system with anti-pulse variable step size algorithm (APV-HANC) is proposed. By using new variable step size method and HANC structure, the APV-HANC method has better tracking and robustness performance of the whole system when impulsive noise occurs. Theoretical analysis and simulations confirms the superior performance of the proposed method.","PeriodicalId":386048,"journal":{"name":"2020 IEEE 6th International Conference on Computer and Communications (ICCC)","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124325358","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 : 2020-12-11DOI: 10.1109/ICCC51575.2020.9345160
Dachuan Zhao
The effect of training of deep neural network depends on the selection of the activation function and the optimizer, because the different activation functions lead to distinct loss curvature and the different optimizers will have different performance in distinct curvatures. In this paper, we select different combinations of activation functions and optimizers, seek to select the best combination under the same experiment setting, and take a general discussion for the efficiency of these combinations finally. Moreover, to guarantee fair comparison the hyperparameters tuning is conducted.
{"title":"On the convergence of optimizer-activation pairs","authors":"Dachuan Zhao","doi":"10.1109/ICCC51575.2020.9345160","DOIUrl":"https://doi.org/10.1109/ICCC51575.2020.9345160","url":null,"abstract":"The effect of training of deep neural network depends on the selection of the activation function and the optimizer, because the different activation functions lead to distinct loss curvature and the different optimizers will have different performance in distinct curvatures. In this paper, we select different combinations of activation functions and optimizers, seek to select the best combination under the same experiment setting, and take a general discussion for the efficiency of these combinations finally. Moreover, to guarantee fair comparison the hyperparameters tuning is conducted.","PeriodicalId":386048,"journal":{"name":"2020 IEEE 6th International Conference on Computer and Communications (ICCC)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126266730","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 : 2020-12-11DOI: 10.1109/ICCC51575.2020.9345098
Yuan Li, Shouxian Mou
A fully integrated Ku-band (14∼18GHz) self-biased bidirectional amplifier (BDA) is demonstrated in a $0.25mumathrm{m}$ GaAs pHEMT technology. The proposed bidirectional amplifier comprises a power amplifier (PA) and a low noise amplifier (LNA) for T/R modules of phased array with in/output switches. In transmitting mode, the BDA achieves a flat small signal gain of $24.2pm 0.8 text{dB}$, the measured saturated output power is 23.6 dBm with 28.3% peak power added efficiency (PAE) at 16 GHz. In receiving mode, the BDA achieves a flat gain of $13.1pm 0.7 text{dB}$. The measured minimum noise figure is 4.2 dB at 16 GHz and below 4.7 dB over the band. And its in/output P1 dB are 10.3 dBm and 22.8 dBm at 16 GHz, respectively. The size of the MMIC is $2.15 text{mm}times 1.55 text{mm}$. To the authors' knowledge, this is the first demonstration of Ku-band self-biased BDA, and it attains state-of-the-art peak PAE in Tx mode, and in/output P1dB in Rx mode.
{"title":"A Ku-Band Self-Biased Bidirectional Amplifier in $0.25 mumathrm{m}$ PHEMT Technology","authors":"Yuan Li, Shouxian Mou","doi":"10.1109/ICCC51575.2020.9345098","DOIUrl":"https://doi.org/10.1109/ICCC51575.2020.9345098","url":null,"abstract":"A fully integrated Ku-band (14∼18GHz) self-biased bidirectional amplifier (BDA) is demonstrated in a $0.25mumathrm{m}$ GaAs pHEMT technology. The proposed bidirectional amplifier comprises a power amplifier (PA) and a low noise amplifier (LNA) for T/R modules of phased array with in/output switches. In transmitting mode, the BDA achieves a flat small signal gain of $24.2pm 0.8 text{dB}$, the measured saturated output power is 23.6 dBm with 28.3% peak power added efficiency (PAE) at 16 GHz. In receiving mode, the BDA achieves a flat gain of $13.1pm 0.7 text{dB}$. The measured minimum noise figure is 4.2 dB at 16 GHz and below 4.7 dB over the band. And its in/output P1 dB are 10.3 dBm and 22.8 dBm at 16 GHz, respectively. The size of the MMIC is $2.15 text{mm}times 1.55 text{mm}$. To the authors' knowledge, this is the first demonstration of Ku-band self-biased BDA, and it attains state-of-the-art peak PAE in Tx mode, and in/output P1dB in Rx mode.","PeriodicalId":386048,"journal":{"name":"2020 IEEE 6th International Conference on Computer and Communications (ICCC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126467721","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 : 2020-12-11DOI: 10.1109/ICCC51575.2020.9344941
Han Liu, Heng Luo, Tingfei Zhang, Wenxuan Huang
Human beings nowadays spend more than 90% of the lifetime indoors, leading to the dramatic increase of energy consumption in various buildings. Therefore, research regarding the environment friendly building becomes much more popular recently in which the prediction of energy consumption is a promised method. Nevertheless, the accuracy of prediction is not sound due to insufficient samples. A novel data generation model, termed HMSP, based on the generative adversarial networks, is proposed in this paper to generate much more data robustly, depending on a small number of samples available. The prediction CV-RMSE results, adopting data from the hybrid model, reach 3.03% at best and 7.99% at worst respectively compared to the samples recorded.
{"title":"A Hybrid Mode of Sequence Prediction Based on Generative Adversarial Network","authors":"Han Liu, Heng Luo, Tingfei Zhang, Wenxuan Huang","doi":"10.1109/ICCC51575.2020.9344941","DOIUrl":"https://doi.org/10.1109/ICCC51575.2020.9344941","url":null,"abstract":"Human beings nowadays spend more than 90% of the lifetime indoors, leading to the dramatic increase of energy consumption in various buildings. Therefore, research regarding the environment friendly building becomes much more popular recently in which the prediction of energy consumption is a promised method. Nevertheless, the accuracy of prediction is not sound due to insufficient samples. A novel data generation model, termed HMSP, based on the generative adversarial networks, is proposed in this paper to generate much more data robustly, depending on a small number of samples available. The prediction CV-RMSE results, adopting data from the hybrid model, reach 3.03% at best and 7.99% at worst respectively compared to the samples recorded.","PeriodicalId":386048,"journal":{"name":"2020 IEEE 6th International Conference on Computer and Communications (ICCC)","volume":"327 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115766828","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}
Taking baseline distance and corner consistency of checkerboard calibration board as objects and combining stereo matching algorithm, the influence of baseline distance and corner consistency on camera calibration and binocular vision locating error is analyzed through building binocular vision locating system. The results show that the calibration error decreases with the increase of angular consistency and baseline distance, and finally tends to be stable. Under the condition of the same baseline distance, the locating error decreases with the increase of angular consistency. The calibration plate with large angular consistency has better locating error stability. The research has practical value for the design of binocular vision locating system's baseline distance and angular consistency.
{"title":"Effect of Baseline Distance and Corner Consistency on Binocular Visual Locating","authors":"Peng Li, Changyou Zhang, Jiachao Peng, Ying Ding, Jinqing Zhan","doi":"10.1109/ICCC51575.2020.9345063","DOIUrl":"https://doi.org/10.1109/ICCC51575.2020.9345063","url":null,"abstract":"Taking baseline distance and corner consistency of checkerboard calibration board as objects and combining stereo matching algorithm, the influence of baseline distance and corner consistency on camera calibration and binocular vision locating error is analyzed through building binocular vision locating system. The results show that the calibration error decreases with the increase of angular consistency and baseline distance, and finally tends to be stable. Under the condition of the same baseline distance, the locating error decreases with the increase of angular consistency. The calibration plate with large angular consistency has better locating error stability. The research has practical value for the design of binocular vision locating system's baseline distance and angular consistency.","PeriodicalId":386048,"journal":{"name":"2020 IEEE 6th International Conference on Computer and Communications (ICCC)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115982051","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}
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