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Enhancing privacy protection in intelligent and connected vehicles: a styleGAN3-based image desensitization dataset and framework 4

Enhancing privacy protection in intelligent and connected ve...

引用

4th International Conference on Advanced Algorithms and Neural Networks, AANN 2024

作者： Wang, Jingyan Wang, Liyong Ji, Haojie Fang, Junzhe Guo, Teng Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science & Technology University No.12 Xiaoying East Road Haidian District Beijing100192 China Zaozhuang Network Security Center No. 2621 Guangming Avenue Xuecheng District Shandong Province 277020 China

ISBN: (纸本)9781510686106

Intelligent and connected vehicles (ICVs) collect vast video footage, inadvertently capturing privacy-sensitive data. To address this, we introduce the IDD-ICV dataset, featuring diverse in-vehicle camera footage. To protect privacy, we propose a styleGAN3 based framework that integrates MHA (Multi-Head Attention) for detecting and desensitizing facial data in datasets. This approach ensures compliance with data security standards and enhances ICVs' privacy protection capabilities during the life cycle of data. Our study contributes to the development of secure and trustworthy autonomous transportation systems by demonstrating the effectiveness of our framework in safeguarding privacy-sensitive information. © 2024 SPIE.

关键词： Differential privacy

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A STUDY OF AIRCRAFT SKIN ASSEMBLY GAP measurement BASED ON POINT CLOUD DATA 9

A STUDY OF AIRCRAFT SKIN ASSEMBLY GAP MEASUREMENT BASED ON P...

引用

9th International Symposium on Test Automation and Instrumentation, ISTAI 2022

作者： Liu, Yongqiang Wu, Guoxin He, Xuejun Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China AVIC Changcheng Institute of Metrology & Mesurement Beijing China

ISBN: (纸本)9781839538391

Aircraft skin is an important large thin-walled component of the fuselage and its high quality assembly is essential to ensure the safety and reliability of the aircraft. Aiming at the problems of high accuracy requirements for measurement of skin assembly gap, low efficiency of manual measurement and difficult to maintain accuracy. Based on contactless digital measurement technology, this paper proposes a method to process and analyse the point cloud data that forms the 3D model of the component, so as to realize the assembly gap measurement. Firstly, a statistical filter is used to remove the outlier noise in the part point cloud model away from the main point cloud;secondly, a voxel filter is used to remove the small-scale noise mixed in the main point cloud;thirdly, the part edge feature points are extracted based on the normal vector information of the point cloud, and finally, the multilinear gap measurement is implemented based on the short distance finding algorithm proposed in this paper, and the results are briefly analysed. Experiments have been conducted using actual data combined with simulation data to verify the feasibility of the method and to provide an outlook on it. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Fuselages

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SIGNIFICANCE ANALYSIS OF INFLUENCE OF SECTION SHAPE ON MAGNETIC FIELD UNIFORMITY OF WEAR PARTICLES DETECTION 9

SIGNIFICANCE ANALYSIS OF INFLUENCE OF SECTION SHAPE ON MAGNE...

引用

9th International Symposium on Test Automation and Instrumentation, ISTAI 2022

作者： Chen, Tao Jia, Ran Tang, Changliang Zhang, Qianqian Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China Army Equipment Project Management Center Beijing China

ISBN: (纸本)9781839538391

Magnetic uniformity is an important factor determining performance of wear particle detection sensors. Taking inner radius of the sensor as reference, dimensionless form factors were proposed to eliminate the dimensional effect on magnetic uniformity. Parametric finite element model was constructed, and the magnetic distribution was obtained by solving Poisson equation satisfied by magnetic vector potential. Evaluation indexes of axial, radial and integrated magnetic uniformity were proposed, and the optimal regression model was derived with section shape factor as independent variable to determine significant degree of influence of section shape on magnetic uniformity. The results show that the long straight sensor has radial magnetic uniformity higher than 90%, and the short thick sensor has axial uniformity higher than 92% under constant turns. The lengthradius ratio has a positive effect on both radial and axial uniformity, and had the most significant effect on radial uniformity. The thickness-radius ratio has a positive and negative effects on radial and axial uniformity, respectively, and had the most significant effect on axial uniformity. The thickness-radius ratio has the most significant effect on integrated uniformity, while inner radius has no significant effect on the uniformity. Increasing the positive effect factor and decreasing the negative effect factor will improve the uniformity. The analysis can provide technical assistance in improving detection performance of the wear particles online detection and optimizing structure design of the sensor. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Finite element method

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Review of research on occlusion issues in RGB-D dynamic scene 3D reconstruction

Review of research on occlusion issues in RGB-D dynamic scen...

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10th International Symposium on Test Automation & Instrumentation (ISTAI 2024)

作者： Yuanqiu Dong Guoxin Wu Guolong Zhang Linglong Zhou Yinyan Qi The Ministry of Education Key Laboratory of Modern Measurement and Control Technology Beijing Information Science & Technology University Beijing People's Republic of China

ISBN: (数字)9781837241910

As innovation proceeds to advance, 3D recreation innovation has ended up a critical portion of the field of computer vision. Among these, 3D reproduction innovation based on RGB-D information sources has ended up a well known approach in later a long time. Right now, the more develop inactive 3D recreation calculations have ended up progressively successful for reproducing stationary objects. Be that as it may, their adequacy lessens when parts of the scene are blocked. This paper briefly presents particular approaches to address impediment issues and the fundamental concepts of energetic 3D remaking innovation based on RGB-D information sources. The points of interest and current investigate status of energetic 3D reproduction focusing on impediment issues utilizing RGB-D information sources are examined. Moreover, the most recent progressions in 3D remaking of energetic scenes are summarized, and proposed future investigate bearings.

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Research on double cubic interpolation combined with Gaussian fitting sub-pixel edge detection method

Research on double cubic interpolation combined with Gaussia...

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10th International Symposium on Test Automation & Instrumentation (ISTAI 2024)

作者： Yinyan Qi Guoxin Wu Yao Li Yuanqiu Dong The Ministry of Education Key Laboratory of Modern Measurement and Control Technology Beijing Information Science & Technology University Beijing People's Republic of China

ISBN: (数字)9781837241910

With the rapid advancements in intelligent manufacturing technology, the realization of fast and accurate measurements in aerospace, instrumentation, machinery and equipment, automotive electronics, and other sectors has become a research hotspot. Image positioning technology and edge detection methods, with their advantages of being fast, non-contact, and precise, have been widely employed. How to improve the accuracy of image measurement lies in solving the problem of accurate positioning of image edge detection, based on the problem of inaccurate extraction of directional information and large error in contour size of image edge detection technology proposes an improved sub-pixel edge detection algorithm with Gaussian fitting by double cubic interpolation. Based on preprocessing for pixel-level edge feature extraction, pixel-level edge points are acquired utilizing the least squares fitting algorithm. The normal section is determined by computing the normal intercept line, while the normal isometric line is identified through the Gaussian integration method. Sub-pixel fitting points are obtained via boundary fitting, and the final grey value is derived using an edge detection algorithm that combines double cubic interpolation and Gaussian fitting on the fitted points. The experimental results demonstrate that, through comparative testing of this method, it has been verified that it exhibits the highest image quality and is superior to most current algorithms. An improvement in the algorithm by 0.021%, 0.025%, and 0.031% in edge localization accuracy compared to the Zernike moment algorithm, Gaussian fitting algorithm, and bicubic interpolation algorithm has been achieved, effectively verifying that the image quality detected by this method is relatively high. In comparison with the point cloud method regarding fitting error, it was observed that the error index increased by 0.025% under strong burst light conditions, 0.026% under normal burst light conditions, an

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Fault diagnosis method based on the timesnet model under variable speed and strong noise

Fault diagnosis method based on the timesnet model under var...

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10th International Symposium on Test Automation & Instrumentation (ISTAI 2024)

作者： Wan Qiao Xiuli Liu Jinpeng Huang Guoxin Wu Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing People's Republic of China

ISBN: (数字)9781837241910

Aiming at the fault diagnosis of rotating machinery in industrial production, which faces the problems of signal noise, variable speed and other interferences that lead to inconspicuous fault features, and the traditional methods rely on manual experience for feature extraction and lack of robustness, the present study introduces a novel fault diagnosis approach utilizing the TimesNet model. This method takes the temporal multi-periodicity as the starting point, and the one-dimensional original signal is divided into multiple two-dimensional signals by different sizes of the period respectively. Subsequently, Inception-Attention modeling is applied to extract intricate time and space information. The experiments use the planetary gearbox dataset to verify the influence of different parameters and structures of TimesNet on the diagnostic effect, and carry out comparative tests with five time-series classification models, which provide some reference value for the application of TimesNet in fault diagnosis.

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The adaptive MPC controller of autonomous driving formula for trajectory tracking

The adaptive MPC controller of autonomous driving formula fo...

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10th International Symposium on Test Automation & Instrumentation (ISTAI 2024)

作者： Bowen Chen Qinghua Su Yue Song Zehao Yin Liyong Wang Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science & Technology University Beijing People's Republic of China

ISBN: (数字)9781837241910

Autonomous driving technology has gradually been applied in real life, and it has also been improved in the China Collegiate Electric Vehicle Racing. However, as one of the critical components of autonomous driving technology, trajectory tracking control still faces challenges. This paper designs a trajectory tracking controller by building a vehicle's three-degree-of-freedom dynamics model and adopting adaptive model predictive control. It adjusts the prediction horizon of the vehicle's trajectory tracking controller in real-time based on the curvature of the desired trajectory to improve the effect of trajectory tracking. Experimental results show that the tracking effect of the adaptive prediction time-domain trajectory tracking controller in the S-curve is improved by 4.97% and 11.36% compared to the fixed prediction time-domain trajectory tracking controller, respectively. For the formula track conditions, the tracking effect of the controller proposed in this paper is improved by 0.71% compared to the fixed prediction time-domain trajectory tracking controller, with an average tracking error of 5.65%.

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Research on three-dimensional fusion method of surveillance video in smart park

Research on three-dimensional fusion method of surveillance ...

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10th International Symposium on Test Automation & Instrumentation (ISTAI 2024)

作者： Haowei Li Yunbo Zuo Huan Hu Sai Chen Yifan Zheng Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing People's Republic of China

ISBN: (数字)9781837241910

The three-dimensional video fusion technology is increasingly becoming an important part of smart parks. In previous security work, surveillance videos are typically displayed in a multi-screen layout, making it difficult to directly analyze the spatial positions of scenes and objects in the monitoring footage. Based on this, a real-time fusion rendering method for RTSP video streams and three-dimensional park models is proposed, which uses texture projection to integrate real videos into virtual three-dimensional models, achieving the fusion of multiple video sources. For scenarios with multiple videos at the same location, a viewpoint-based weighted method is adopted to achieve texture overlay rendering. Finally, a smart park surveillance video fusion platform is built based on the *** framework, supporting real-time rendering on the web. The system also provides various interaction methods, including roaming and viewpoint switching, making it convenient for personnel to monitor key areas. Simultaneously, it achieves the effect of roaming in virtual three-dimensional scenes, enhancing the stereoscopic presentation of real scenes in surveillance videos. The system demonstration proves that effectively combining real-time surveillance videos with three-dimensional models results in better spatial presentation of videos and enhances the ability to discern the actual positions of scenes within the smart park.

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Research on gait recognition by using 1DCNN based on lower limb kinematic posture data

Research on gait recognition by using 1DCNN based on lower l...

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10th International Symposium on Test Automation & Instrumentation (ISTAI 2024)

作者： Mu Li Chao Ma Shaohong Wang Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing People's Republic of China

ISBN: (数字)9781837241910

Gait recognition refers to the process of realizing the detection of human identity or health status and other information according to the characteristics of human plantar pressure, video images or human dynamics indicators. With the advantages of non-contact, non-aggression, no need for cooperation and easy to collect, gait recognition technology has been widely used in recent years in the field of public security criminal investigation, medical care, intelligent transportation and other fields. In this study, to meet the needs of gait recognition, IMU sensors are used to acquire human lower limb motion posture data and wavelet transform is used to decompose several components. Then the components were determined and the optimized 1DCNN model is used to carry out gait recognition research. The results showed that the optimized 1DCNN model for gait recognition task exhibits excellent performance with up to 95% accuracy, 96% recall and F1 value, as well as good computational efficiency, which is valuable for clinical automatic gait recognition analysis, rehabilitation engineering and criminal investigation work. Although there are some errors in some gait classifications, our study provides directions for further optimization of the algorithm to improve the accuracy and robustness of gait recognition.

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Smoking behavior detection based on improved YOLOv7 object association

Smoking behavior detection based on improved YOLOv7 object a...

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10th International Symposium on Test Automation & Instrumentation (ISTAI 2024)

作者： Sai Chen Yunbo Zuo Huan Hu Yifan Zheng Haowei Li Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing People's Republic of China

ISBN: (数字)9781837241910

To address the security risks caused by unauthorized individuals smoking in public places, a method for detecting smoking behavior based on an improved YOLOv7 target association is proposed. First, the improved YOLOv7 algorithm is used to detect the people and cigarette targets in the image, and then the distance relationship between the center coordinates of the cigarette target detection frame and the person target detection box is calculated, and the correlation between the two is located to determine whether there is smoking behavior. The improved YOLOv7 algorithm introduces the CBAM attention module to prioritize key areas and diminish background interference. Simultaneously, the SIOU loss function is employed to bolster the precision of the regression outcomes. Experiments conducted on the test dataset reveal that the proposed approach achieves an accuracy of 91.35% and a detection speed of 78 FPS, achieving real-time accurate detection effects.

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