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Conference on Optics and Communication Technology最新文献

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3D human pose estimation using aided constraints of physiological and action feature 基于生理和动作特征辅助约束的三维人体姿态估计
Conference on Optics and Communication Technology Pub Date : 2022-11-18 DOI: 10.1117/12.2653807
Xianggang Zhang, Lun-ting Zhang, Jiajun Yu, Jing Zeng
{"title":"3D human pose estimation using aided constraints of physiological and action feature","authors":"Xianggang Zhang, Lun-ting Zhang, Jiajun Yu, Jing Zeng","doi":"10.1117/12.2653807","DOIUrl":"https://doi.org/10.1117/12.2653807","url":null,"abstract":"3D human pose estimation is a hot research topic at present, and it also has a wide application potential. The inherent uncertainty and multiple solutions of 2D to 3D mapping based on a single image limit the accuracy of 3D human pose estimation. Considering that human posture is affected by physiological features and motion states, the network design in this paper uses physiological and motion features to provide constraints for posture estimation, in order to achieve better accuracy. Specifically, in the network design of this paper, three auxiliary judgment networks, namely gender, motion type and true false judgment, are used to further constrain the generated posture. Moreover, experiments on Human3.6M dataset show that the accuracy of mapping 2D joint coordinates to 3D pose coordinates can be effectively improved by introducing constraints of physiological features and motion states.","PeriodicalId":253792,"journal":{"name":"Conference on Optics and Communication Technology","volume":"199 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123519469","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
Optical fiber interference magnetic field sensor based on Terfenol-D magnetostrictive material 基于Terfenol-D磁致伸缩材料的光纤干涉磁场传感器
Conference on Optics and Communication Technology Pub Date : 2022-11-18 DOI: 10.1117/12.2654064
F. Peng, Wei Qiang, Fan Zhang, Min Luo, Jian Wang, Wenyi Ren, Qi Wu
{"title":"Optical fiber interference magnetic field sensor based on Terfenol-D magnetostrictive material","authors":"F. Peng, Wei Qiang, Fan Zhang, Min Luo, Jian Wang, Wenyi Ren, Qi Wu","doi":"10.1117/12.2654064","DOIUrl":"https://doi.org/10.1117/12.2654064","url":null,"abstract":"It is suggested and designed to use Terfenol-D magnetostrictive material in a fiber extrinsic F-P interferometric magnetic field sensor. The two reflective end faces of the F-P cavity are, respectively, the copper reflective layer and the fiber end face. As a result, changes of the magnetic field have an impact on the F-P cavity's cavity length, and the environmental magnetic field can be detected by measuring the variation in cavity length. The typical relationship between magnetic field and spectral drift of the sensor is theoretically analyzed. The sensitivity is measured experimentally to be 0.82 nm/mT for a magnetic field intensity of 0 mT to 70 mT at room temperature. The sensor has a compact structure, and the complexity of the low-level interference signal demodulation makes it suitable for use in engineering.","PeriodicalId":253792,"journal":{"name":"Conference on Optics and Communication Technology","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114947402","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
Fragmented cultural relics restoration based on point cloud data 基于点云数据的碎片化文物修复
Conference on Optics and Communication Technology Pub Date : 2022-11-18 DOI: 10.1117/12.2653801
Yahui Ding, Hongjuan Wang
{"title":"Fragmented cultural relics restoration based on point cloud data","authors":"Yahui Ding, Hongjuan Wang","doi":"10.1117/12.2653801","DOIUrl":"https://doi.org/10.1117/12.2653801","url":null,"abstract":"Three-dimensional scanning technology, graphic image processing, virtual reality and other technologies are an important and inevitable way to protect cultural relics. With the passage of time, most of the cultural relics have been removed. Aiming at the main process of fragmenting cultural relics restoration based on point cloud processing, this paper summarizes the algorithms of 3d data denoising and simplification, model feature extraction, model classification and model assembling in virtual restoration of fragmenting cultural relics.","PeriodicalId":253792,"journal":{"name":"Conference on Optics and Communication Technology","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123863308","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
Assessment algorithm of scene complexity based on X-CENet 基于X-CENet的场景复杂度评估算法
Conference on Optics and Communication Technology Pub Date : 2022-11-18 DOI: 10.1117/12.2653877
Fanshu Shen, Yan Wen, Z. Zuo
{"title":"Assessment algorithm of scene complexity based on X-CENet","authors":"Fanshu Shen, Yan Wen, Z. Zuo","doi":"10.1117/12.2653877","DOIUrl":"https://doi.org/10.1117/12.2653877","url":null,"abstract":"In order to realize the rapid perception of complex scenes, the traditional scene complexity assessment algorithm has strong limitations in feature representation and scope of application, and it is difficult to deal with complex scenes. However, the existing deep network methods are lack of the consideration of the correlation between the underlying features of gray image and the complexity level, and the amount of parameters is too high to meet the needs of rapid response in practical applications. Based on the deep separable convolution module and residual connection structure, this paper designs a lightweight complexity assessment network X-CENet with stronger feature expression ability. A dense connection module which makes full use of multi-level features is introduced to improve the feature expression ability of the network for scene images. The underlying information such as image texture is particularly important for the assessment of complexity, so the feature cascade layer of the head and tail of the main modules is added to strengthen the utilization of the underlying feature information in the network. Experiments show that compared with other deep networks, this method can obtain higher assessment accuracy in the dimensions of image characteristics and detection performance with smaller parameters. Compared with the Inception V3 with similar parameter amount, this method improves the LCC index by 2.849% and the SRCC index by 3.338%.","PeriodicalId":253792,"journal":{"name":"Conference on Optics and Communication Technology","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123905506","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 on segmentation algorithm of rooftop distributed PV arrays based on deep learning 基于深度学习的屋顶分布式光伏阵列分割算法研究
Conference on Optics and Communication Technology Pub Date : 2022-11-18 DOI: 10.1117/12.2653426
M. Guo
{"title":"Research on segmentation algorithm of rooftop distributed PV arrays based on deep learning","authors":"M. Guo","doi":"10.1117/12.2653426","DOIUrl":"https://doi.org/10.1117/12.2653426","url":null,"abstract":"Hot spot detection is a very important aspect in the field of PV plant inspection, and with the development of UAV technology, PV hot spot detection by UAV based on image processing has gradually emerged. To solve this problem, this paper introduces a deep learning model for coarse detection of PV regions to remove background interference, and uses image preprocessing, convolutional operations, morphological operations and Hough line transformation to finally achieve component-level segmentation of PV arrays. The experimental results show that the algorithm of this paper can segment the PV array accurately and quickly, and the effect is better than the traditional segmentation algorithm.","PeriodicalId":253792,"journal":{"name":"Conference on Optics and Communication Technology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125877933","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
Category pattern mining based image retrieval 基于分类模式挖掘的图像检索
Conference on Optics and Communication Technology Pub Date : 2022-11-18 DOI: 10.1117/12.2653732
Hu He, Guoxin Hao, Bin Wen
{"title":"Category pattern mining based image retrieval","authors":"Hu He, Guoxin Hao, Bin Wen","doi":"10.1117/12.2653732","DOIUrl":"https://doi.org/10.1117/12.2653732","url":null,"abstract":"Image retrieval is to find out the similar semantic images to the query image, which is an important task in the field of image recognition. It is still an open challenging task due to the semantic gap of image understanding. The traditional image retrieval method is a simple retrieval between the query image and the database. However, only a query image contains weaker category information, so that the traditional image-based retrieval results are not satisfactory. In this paper, we propose a category pattern mining (CPM) strategy to extend an image (point) to an image category (plane). It means the semantic extension is performed from the individual query image to the whole image category. The proposed PTP (point to plane) method mined the category pattern of the query image and enriched the semantic information. The main contribution of the PTP framework is to improve the image retrieval from the traditional image-based retrieval into the new category-based retrieval. Experimental results and evaluations on two databases demonstrate that the proposed PTP method achieves an obvious superiority in the image retrieval tasks.","PeriodicalId":253792,"journal":{"name":"Conference on Optics and Communication Technology","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129960861","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
Power image classification algorithm based on improved collaborative representation 基于改进协同表示的功率图像分类算法
Conference on Optics and Communication Technology Pub Date : 2022-11-18 DOI: 10.1117/12.2654055
Hongwei Wu, Zhihao Tang
{"title":"Power image classification algorithm based on improved collaborative representation","authors":"Hongwei Wu, Zhihao Tang","doi":"10.1117/12.2654055","DOIUrl":"https://doi.org/10.1117/12.2654055","url":null,"abstract":"As a typical linear representation method, collaborative representation has become an important research direction in the field of power image classification. Traditional cooperative representation algorithms often ignore the competitiveness and distinguish ability of each kind of samples, which affects the performance of power image classification. In order to further improve the accuracy of power equipment image recognition, this paper proposes an image classification algorithm based on improved cooperative representation, which makes full use of the competition between each kind of samples and the local geometric structure characteristics of samples. Experiments on power image data sets with and without noise show that the proposed algorithm has good classification performance.","PeriodicalId":253792,"journal":{"name":"Conference on Optics and Communication Technology","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121650216","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
Imaging comparison of time and frequency domain methods for low frequency UWB BSAR 低频超宽带BSAR时域和频域成像方法的比较
Conference on Optics and Communication Technology Pub Date : 2022-11-18 DOI: 10.1117/12.2653467
Hongtu Xie, Xiao Hu, Jiaxing Chen, Peng Zou, Guoqian Wang
{"title":"Imaging comparison of time and frequency domain methods for low frequency UWB BSAR","authors":"Hongtu Xie, Xiao Hu, Jiaxing Chen, Peng Zou, Guoqian Wang","doi":"10.1117/12.2653467","DOIUrl":"https://doi.org/10.1117/12.2653467","url":null,"abstract":"Low frequency ultra-wideband bistatic synthetic aperture radar (UWB BSAR) not only gets the high-resolution image and increase the scatter information, but also has the well ability of the foliage penetrating, which is potential of detecting the concealed target under the vegetation. This paper studies the performance of the back-projection (BP) algorithm in the time domain and range-Doppler (RD) algorithm in the frequency domain for the low frequency UWB BSAR imaging. First, the basic flow of the BP algorithm and RD algorithm for the low frequency UWB BSAR imaging is deduced. Then, the quality and efficiency of two algorithms for the low frequency UWB BSAR imaging are investigated. Finally, the two algorithms are tested based on the low frequency UWB BSAR simulation data, and the imaging performance of the two algorithms is compared and analyzed. The experiment results prove the correctness of the theoretical analysis and the effectiveness of the proposed methods.","PeriodicalId":253792,"journal":{"name":"Conference on Optics and Communication Technology","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130324617","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
Design concept of sign language recognition translation and gesture recognition control system based on deep learning and machine vision 基于深度学习和机器视觉的手语识别翻译与手势识别控制系统的设计理念
Conference on Optics and Communication Technology Pub Date : 2022-11-18 DOI: 10.1117/12.2653702
Yiyang Zhang, X. Pu, Xiaolu Wang, Haopeng Guo, Ke Liu, Qian-Ying Yang, Lili Wang
{"title":"Design concept of sign language recognition translation and gesture recognition control system based on deep learning and machine vision","authors":"Yiyang Zhang, X. Pu, Xiaolu Wang, Haopeng Guo, Ke Liu, Qian-Ying Yang, Lili Wang","doi":"10.1117/12.2653702","DOIUrl":"https://doi.org/10.1117/12.2653702","url":null,"abstract":"With the development of society, gestures are used in many aspects, but the computer's functionality for gesture recognition is still to be improved. This article is mainly a preliminary idea of a basic gesture recognition system built based on the existing Google deep learning framework TensorFlow and gesture recognition components in MediaPipe and OpenCv machine vision open-source library. The training dataset is first subjected to skeleton key point coordinate extraction, then the pre-processed dataset is used to train the neural network and constitute the preliminary model, and finally the model is corrected and changed in the end.","PeriodicalId":253792,"journal":{"name":"Conference on Optics and Communication Technology","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131164275","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
Design of infrared sensor for vehicle rainfall based on ZEMAX 基于ZEMAX的车载降雨红外传感器设计
Conference on Optics and Communication Technology Pub Date : 2022-11-18 DOI: 10.1117/12.2653763
M. Liang, Yue Zhou, Tiantai Zheng, Lin Wang, Lize Ming, Jichong Han, Haiyang Sun
{"title":"Design of infrared sensor for vehicle rainfall based on ZEMAX","authors":"M. Liang, Yue Zhou, Tiantai Zheng, Lin Wang, Lize Ming, Jichong Han, Haiyang Sun","doi":"10.1117/12.2653763","DOIUrl":"https://doi.org/10.1117/12.2653763","url":null,"abstract":"The optical structure design and simulation of vehicle rainfall sensor are carried out with ZEMAX. Two groups of six infrared LED for star-shaped layout. The design of incident Angle of infrared pulse light is greater than the critical angle of total reflection when there is no rain and each group of infrared LED works at a certain time sequence. The rainwater on the windshield of the car changes the refractive index of the emitting medium of the pulsed infrared ray, which causes the attenuation of the luminous flux of the receiver's infrared ray and the detection circuit will generate impulse signal. Using fast Fourier transform and fuzzy control technology, the output signal of different windshield rainfall is given, and the output signal is communicated with the body control computer by the built-in LIN bus module of the single-chip microcomputer, so as to realize the automatic control of the windshield wiper in the driving rain and accidental muddy water splashing.","PeriodicalId":253792,"journal":{"name":"Conference on Optics and Communication Technology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128464908","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
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