IEEE Journal of Indoor and Seamless Positioning and Navigation最新文献_第4页

A Novel Cross-Attention-Based Pedestrian Visual–Inertial Odometry With Analyses Demonstrating Challenges in Dense Optical Flow 一种基于交叉注意力的新型行人视觉惯性轨迹测量法，其分析表明了密集光流所面临的挑战

IEEE Journal of Indoor and Seamless Positioning and Navigation Pub Date : 2023-12-18 DOI: 10.1109/JISPIN.2023.3344077

Ilari Pajula;Niclas Joswig;Aiden Morrison;Nadia Sokolova;Laura Ruotsalainen

{"title":"A Novel Cross-Attention-Based Pedestrian Visual–Inertial Odometry With Analyses Demonstrating Challenges in Dense Optical Flow","authors":"Ilari Pajula;Niclas Joswig;Aiden Morrison;Nadia Sokolova;Laura Ruotsalainen","doi":"10.1109/JISPIN.2023.3344077","DOIUrl":"https://doi.org/10.1109/JISPIN.2023.3344077","url":null,"abstract":"Visual–inertial odometry (VIO), the fusion of visual and inertial sensor data, has been shown to be functional for navigation in global-navigation-satellite-system-denied environments. Recently, dense-optical-flow-based end-to-end trained deep learning VIO models have gained superior performance in outdoor navigation. In this article, we introduced a novel visual–inertial sensor fusion approach based on vision transformer architecture with a cross-attention mechanism, specifically designed to better integrate potentially poor-quality optical flow features with inertial data. Although optical-flow-based VIO models have obtained superior performance in outdoor vehicle navigation, both in accuracy and ease of calibration, we have shown how their suitability for indoor pedestrian navigation is still far from existing feature-matching-based methods. We compare the performance of traditional VIO models against deep-learning-based VIO models on the KITTI benchmark dataset and our custom pedestrian navigation dataset. We show how end-to-end trained VIO models using optical flow were significantly outperformed by simpler visual odometry models utilizing feature matching. Our findings indicate that due to the robustness against occlusion and camera shake, feature matching is better suited for indoor pedestrian navigation, whereas dense optical flow remains viable for vehicular data. Therefore, the most feasible way forward will be the integration of our novel model with feature-based visual data encoding.","PeriodicalId":100621,"journal":{"name":"IEEE Journal of Indoor and Seamless Positioning and Navigation","volume":"2 ","pages":"25-35"},"PeriodicalIF":0.0,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10363184","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139406582","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Spoofing Evident and Spoofing Deterrent Localization Using Ultrawideband (UWB) Active–Passive Ranging 利用超宽带 (UWB) 有源-无源测距进行欺骗识别和欺骗威慑定位

IEEE Journal of Indoor and Seamless Positioning and Navigation Pub Date : 2023-12-14 DOI: 10.1109/JISPIN.2023.3343336

Haige Chen;Ashutosh Dhekne

{"title":"Spoofing Evident and Spoofing Deterrent Localization Using Ultrawideband (UWB) Active–Passive Ranging","authors":"Haige Chen;Ashutosh Dhekne","doi":"10.1109/JISPIN.2023.3343336","DOIUrl":"https://doi.org/10.1109/JISPIN.2023.3343336","url":null,"abstract":"This article presents UnSpoof, an ultrawideband localization system that can detect and localize distance-spoofing tags with a few collaborative passively receiving anchors. We propose novel formulations that enable passively receiving anchors to deduce their time-of-flight (ToF) and time-difference-of-arrival (TDoA) just by overhearing standard two-way ranging messages between the tag and one active anchor. Our ToF formulation can be used to precisely localize an honest tag, and to detect a distance-spoofing tag that falsely reports its timestamps. Additionally, our TDoA formulation enables spoofing deterrent localization, which can be used to track down and apprehend a malicious tag. Our experimental evaluation shows a 30-cm \u0000<inline-formula><tex-math>$text {75}{text{th}}$</tex-math></inline-formula>\u0000 percentile error for ToF-based honest tag localization and a submeter error for TDoA-based localization for spoofing tags. We demonstrate successful detection of distance reduction and enlargement attacks inside the anchors' convex hull and graceful degradation outside. In addition, we show the effects of a nonregular geometry of anchors and invite researchers and practitioners to experiment with anchor topologies of interest to them via our open source modeling software.","PeriodicalId":100621,"journal":{"name":"IEEE Journal of Indoor and Seamless Positioning and Navigation","volume":"2 ","pages":"12-24"},"PeriodicalIF":0.0,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10360231","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139081260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

PoE-Enabled Visible Light Positioning Network With Low Bandwidth Requirement and High Precision Pulse Reconstruction 支持 PoE 的可见光定位网络，带宽要求低，脉冲重建精度高

IEEE Journal of Indoor and Seamless Positioning and Navigation Pub Date : 2023-12-13 DOI: 10.1109/JISPIN.2023.3342732

Zhenghai Wang;Xuan Huang;Xuanbang Chen;Mengzhen Xu;Xiaodong Liu;Yuhao Wang;Xun Zhang

{"title":"PoE-Enabled Visible Light Positioning Network With Low Bandwidth Requirement and High Precision Pulse Reconstruction","authors":"Zhenghai Wang;Xuan Huang;Xuanbang Chen;Mengzhen Xu;Xiaodong Liu;Yuhao Wang;Xun Zhang","doi":"10.1109/JISPIN.2023.3342732","DOIUrl":"https://doi.org/10.1109/JISPIN.2023.3342732","url":null,"abstract":"The power over Ethernet (PoE)-enabled visible light positioning (VLP) networks as a promising technology can significantly enhance accuracy and cost-effectiveness of indoor positioning. However, both the limited bandwidth of the light-emitting diode (LED) and the low sampling rate of the receiver have a negative impact on the positioning performance. Moreover, time synchronization requirements between transmitters and between transceivers become more stringent in a resource-constrained VLP network. To address these issues, a PoE-enabled VLP scheme with low bandwidth requirement and high-precision pulse reconstruction is proposed in this article. Specifically, the precision time protocol and synchronous Ethernet are introduced to realize the synchronization transmission. Meanwhile, an \u0000<sc>on–off</small>\u0000 keying (OOK) modulation-based beacon signal is designed to unlock both the transceivers' synchronization and bandwidth requirements. Then, a high-precision pulse reconstruction method considering the LED model and impulse response is established to enhance the signal quality. Moreover, the position is estimated based on the maximum a posteriori (MAP) probability criterion. Experimental results obtained by the VLP testbed demonstrate that the proposed scheme outperforms the benchmark positioning schemes. It achieves a positioning accuracy of 1.7 cm by using the reconstructed 2 GHz sampling rate in the case of a bandwidth of 50 MHz and a real sampling rate of 100 MHz. Last but not least, the proposed scheme maintains positioning accuracy within 30 cm even with a few MHz bandwidth of LED.","PeriodicalId":100621,"journal":{"name":"IEEE Journal of Indoor and Seamless Positioning and Navigation","volume":"2 ","pages":"1-11"},"PeriodicalIF":0.0,"publicationDate":"2023-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10356613","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139081274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Real-Time Object Pose Tracking System With Low Computational Cost for Mobile Devices 低计算成本的移动设备实时物体姿态跟踪系统

IEEE Journal of Indoor and Seamless Positioning and Navigation Pub Date : 2023-12-11 DOI: 10.1109/JISPIN.2023.3340987

Yo-Chung Lau;Kuan-Wei Tseng;Peng-Yuan Kao;I-Ju Hsieh;Hsiao-Ching Tseng;Yi-Ping Hung

{"title":"Real-Time Object Pose Tracking System With Low Computational Cost for Mobile Devices","authors":"Yo-Chung Lau;Kuan-Wei Tseng;Peng-Yuan Kao;I-Ju Hsieh;Hsiao-Ching Tseng;Yi-Ping Hung","doi":"10.1109/JISPIN.2023.3340987","DOIUrl":"https://doi.org/10.1109/JISPIN.2023.3340987","url":null,"abstract":"Real-time object pose estimation and tracking is challenging but essential for some emerging applications, such as augmented reality. In general, state-of-the-art methods address this problem using deep neural networks, which indeed yield satisfactory results. Nevertheless, the high computational cost of these methods makes them unsuitable for mobile devices where real-world applications usually take place. We propose real-time object pose tracking system with low computational cost for mobile devices. It is a monocular inertial-assisted-visual system with a client–server architecture connected by high-speed networking. Inertial measurement unit (IMU) pose propagation is performed on the client side for fast pose tracking, and RGB image-based 3-D object pose estimation is performed on the server side to obtain accurate poses, after which the pose is sent to the client side for refinement, where we propose a bias self-correction mechanism to reduce the drift. We also propose a fast and effective pose inspection algorithm to detect tracking failures and incorrect pose estimation. In this way, the pose updates rapidly even within 5 ms on low-level devices, making it possible to support real-time tracking for applications. In addition, an object pose dataset with RGB images and IMU measurements is delivered for evaluation. Experiments also show that our method performs well with both accuracy and robustness.","PeriodicalId":100621,"journal":{"name":"IEEE Journal of Indoor and Seamless Positioning and Navigation","volume":"1 ","pages":"211-220"},"PeriodicalIF":0.0,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10352604","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138822151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Practical and Parameterized Fingerprinting Through Maximal Filtering for Indoor Positioning 通过最大过滤实现实用的参数化指纹识别，用于室内定位

IEEE Journal of Indoor and Seamless Positioning and Navigation Pub Date : 2023-12-08 DOI: 10.1109/JISPIN.2023.3340638

F. Serhan Daniş

{"title":"Practical and Parameterized Fingerprinting Through Maximal Filtering for Indoor Positioning","authors":"F. Serhan Daniş","doi":"10.1109/JISPIN.2023.3340638","DOIUrl":"https://doi.org/10.1109/JISPIN.2023.3340638","url":null,"abstract":"Fingerprinting techniques are known to perform better for radio-frequency-based indoor positioning compared to lateration-based techniques. However, accurate fingerprinting depends on a thorough prior scene analysis, in which the area should be described in terms of the signal parameters the positioning system deploys. This requires a heavy workload to build accurate systems, causing a tradeoff between accuracy and practicality. In this article, we propose a chain of subsequent preprocessing techniques for generating accurate radio frequency maps (RMs). The techniques consist of filtering the received signal strength indicator and interpolating the local probability distribution parameters. The proposed subsequent techniques generate smoother RMs and describe these maps with only two parameters per position. By plugging an adaptive particle filter as the position estimation algorithm, we show that the generated RMs increase the positioning accuracy significantly. We also investigate the relation between practicality and accuracy in terms of the invested time in the process of fingerprinting and the stored data to represent the RM. Alongside the increased accuracy of the proposed system, the approach allows a dramatic increase in the practicality of the fingerprinting technique.","PeriodicalId":100621,"journal":{"name":"IEEE Journal of Indoor and Seamless Positioning and Navigation","volume":"1 ","pages":"199-210"},"PeriodicalIF":0.0,"publicationDate":"2023-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10349912","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138822032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Ultra-Wideband Localization: Advancements in Device and System Calibration for Enhanced Accuracy and Flexibility 超宽带定位：设备和系统校准方面的进展，以提高准确性和灵活性

IEEE Journal of Indoor and Seamless Positioning and Navigation Pub Date : 2023-12-05 DOI: 10.1109/JISPIN.2023.3339602

Risang Yudanto;Jianqiao Cheng;Erik Hostens;Miel Van der Wilt;Mats Vande Cavey

{"title":"Ultra-Wideband Localization: Advancements in Device and System Calibration for Enhanced Accuracy and Flexibility","authors":"Risang Yudanto;Jianqiao Cheng;Erik Hostens;Miel Van der Wilt;Mats Vande Cavey","doi":"10.1109/JISPIN.2023.3339602","DOIUrl":"https://doi.org/10.1109/JISPIN.2023.3339602","url":null,"abstract":"We show how the state of use of ultra-wideband (UWB) system is improved by removing systematic errors (bias) on device-level to improve accuracy and apply simple procedure to automate calibration process on the system-level to reduce manual efforts. On device-level, we discern the different sources of bias and establish a method that determines their values, for specific hardware and for individual devices. Our comprehensive approach includes simple, easy-to-implement methodologies for compensating these biases, resulting in a significant improvement in ranging accuracy. The mean ranging error has been reduced from 0.15 to 0.007 m, and the three-sigma error margin has decreased from 0.277 to approximately 0.103 m. To demonstrate this, a dedicated test setup was built. On system-level, we developed a method that avoids measuring all anchor positions one by one by exploiting increased redundancy from anchor-to-anchor and anchor-to-tag ranges, and automatically calculating the anchors topology (relative positions between each other). Nonlinear least squares provides the maximum likelihood estimate of the anchor positions and their uncertainty. This approach not only refines the accuracy of tag localization but also offers a predictive measure of its uncertainty, giving users a clearer understanding of the system's capabilities in real-world scenarios. This system-level enhancement is further complemented by the integration of a ranging protocol called automatic UWB ranging any-to-any, which offers additional layers of flexibility, reliability, and ease of deployment to the UWB localization process.","PeriodicalId":100621,"journal":{"name":"IEEE Journal of Indoor and Seamless Positioning and Navigation","volume":"1 ","pages":"242-253"},"PeriodicalIF":0.0,"publicationDate":"2023-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10342852","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139081290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Self-Localizing On-Demand Portable Wireless Beacons for Coverage Enhancement of RF Beacon-Based Indoor Localization Systems 按需自定位便携式无线信标，用于增强基于射频信标的室内定位系统的覆盖范围

IEEE Journal of Indoor and Seamless Positioning and Navigation Pub Date : 2023-12-01 DOI: 10.1109/JISPIN.2023.3338186

Changwei Chen;Solmaz S. Kia

{"title":"Self-Localizing On-Demand Portable Wireless Beacons for Coverage Enhancement of RF Beacon-Based Indoor Localization Systems","authors":"Changwei Chen;Solmaz S. Kia","doi":"10.1109/JISPIN.2023.3338186","DOIUrl":"https://doi.org/10.1109/JISPIN.2023.3338186","url":null,"abstract":"Localization using relative ranging from radio frequency (RF) wireless beacons installed in an indoor infrastructure is becoming the hallmark of indoor localization systems for asset tracking. However, the coverage of these beacons is not always complete. Moreover, installing the beacons in underutilized spaces is not cost-effective. Deploying portable on-demand beacons to extend the coverage is a cost-effective solution for a robust and reliable RF beacon-based localization system. The challenge though is how to localize these deployed beacons. This article presents a decentralized algorithm to allow deployed beacons to self-localize themselves. This solution removes the rigid requirement of the beacon connectivity, and thus, the need to deploy the beacons in a priori known and surveyed locations. The deployed beacons localize themselves in a collaborative and decentralized manner without the necessity of each of them being connected to three preinstalled infrastructure beacons. The proposed solution is a robust deployment method in the sense that if a portable beacon is moved for any reason, it can automatically relocalize itself in the decentralized manner. Simulation studies of the ultrawideband beacon deployment and localization demonstrates the effectiveness and robustness of the proposed solution in terms of the accurate autonomous position estimation for multiple beacons with \u0000<inline-formula><tex-math>$1text{-m}$</tex-math></inline-formula>\u0000 positioning accuracy, and an average error reduction being 79.21% and 34.41% with respect to the conventional methods in literature.","PeriodicalId":100621,"journal":{"name":"IEEE Journal of Indoor and Seamless Positioning and Navigation","volume":"1 ","pages":"180-186"},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10336843","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138822031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

MobLoc: CSI-Based Location Fingerprinting With MUSIC MobLoc：利用音乐进行基于 CSI 的位置指纹识别

IEEE Journal of Indoor and Seamless Positioning and Navigation Pub Date : 2023-11-29 DOI: 10.1109/JISPIN.2023.3336609

Stepan Mazokha;Fanchen Bao;George Sklivanitis;Jason O. Hallstrom

{"title":"MobLoc: CSI-Based Location Fingerprinting With MUSIC","authors":"Stepan Mazokha;Fanchen Bao;George Sklivanitis;Jason O. Hallstrom","doi":"10.1109/JISPIN.2023.3336609","DOIUrl":"https://doi.org/10.1109/JISPIN.2023.3336609","url":null,"abstract":"Many CSI-based localization methods have been proposed over the last decade. Fingerprinting has been one of the highest achieving approaches due to its capacity to capture environmental characteristics that are not readily captured using classic localization mechanisms such as multilateration. However, oftentimes the proposed methods are limited by reliance on large-scale training datasets. Further, methods are rarely evaluated on nonstationary devices, which are the most common in real-world environments. In our work, we address these challenges by introducing MobLoc. We adopt MUSIC pseudospectrum-based fingerprinting, which can benefit from, but does not heavily rely upon a large number of packets for each fingerprint. To evaluate our method, we leverage a publicly available dataset of passively collected CSI measurements, DLoc (Ayyalasomayajula et al., 2020), where an emitter sends signals in motion. We also benchmark MobLoc against a series of state-of-the-art localization methods. The results demonstrate that our method outperforms SpotFi (Kotaru et al., 2015), EntLoc (Chen et al., 2019), and AngLo (Chen et al., 2020), and falls very short of achieving DLoc accuracy. On the DLoc dataset, MobLoc achieves 0.33 m median (and 0.82 m, 90th percentile) localization error in a simple environment and 1.15 m median (2.59 m, 90th percentile) localization error in a complex environment. However, despite MobLoc not exceeding DLoc's accuracy, we consider its performance as a tradeoff for computational resources required to deploy the method in a real-world environment. We anticipate that this advantage will enable the adoption of MobLoc in city-scape localization systems, where the cost of computational resources is key.","PeriodicalId":100621,"journal":{"name":"IEEE Journal of Indoor and Seamless Positioning and Navigation","volume":"1 ","pages":"231-241"},"PeriodicalIF":0.0,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10333260","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139050639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Feasibility Study on Indoor Localization and Multiperson Tracking Using Sparsely Distributed Camera Network With Edge Computing 利用边缘计算的稀疏分布摄像机网络进行室内定位和多人跟踪的可行性研究

IEEE Journal of Indoor and Seamless Positioning and Navigation Pub Date : 2023-11-28 DOI: 10.1109/JISPIN.2023.3337189

Hyeokhyen Kwon;Chaitra Hegde;Yashar Kiarashi;Venkata Siva Krishna Madala;Ratan Singh;ArjunSinh Nakum;Robert Tweedy;Leandro Miletto Tonetto;Craig M. Zimring;Matthew Doiron;Amy D. Rodriguez;Allan I. Levey;Gari D. Clifford

{"title":"A Feasibility Study on Indoor Localization and Multiperson Tracking Using Sparsely Distributed Camera Network With Edge Computing","authors":"Hyeokhyen Kwon;Chaitra Hegde;Yashar Kiarashi;Venkata Siva Krishna Madala;Ratan Singh;ArjunSinh Nakum;Robert Tweedy;Leandro Miletto Tonetto;Craig M. Zimring;Matthew Doiron;Amy D. Rodriguez;Allan I. Levey;Gari D. Clifford","doi":"10.1109/JISPIN.2023.3337189","DOIUrl":"https://doi.org/10.1109/JISPIN.2023.3337189","url":null,"abstract":"Camera-based activity monitoring systems are becoming an attractive solution for smart building applications with the advances in computer vision and edge computing technologies. In this article, we present a feasibility study and systematic analysis of a camera-based indoor localization and multiperson tracking system implemented on edge computing devices within a large indoor space. To this end, we deployed an end-to-end edge computing pipeline that utilizes multiple cameras to achieve localization, body orientation estimation, and tracking of multiple individuals within a large therapeutic space spanning \u0000<inline-formula><tex-math>$text{1700}, text{m}^{2}$</tex-math></inline-formula>\u0000, all while maintaining a strong focus on preserving privacy. Our pipeline consists of 39 edge computing camera systems equipped with tensor processing units (TPUs) placed in the indoor space's ceiling. To ensure the privacy of individuals, a real-time multiperson pose estimation algorithm runs on the TPU of the computing camera system. This algorithm extracts poses and bounding boxes, which are utilized for indoor localization, body orientation estimation, and multiperson tracking. Our pipeline demonstrated an average localization error of 1.41 m, a multiple-object tracking accuracy score of 88.6%, and a mean absolute body orientation error of 29\u0000<inline-formula><tex-math>$^{circ }$</tex-math></inline-formula>\u0000. These results show that localization and tracking of individuals in a large indoor space is feasible even with the privacy constrains.","PeriodicalId":100621,"journal":{"name":"IEEE Journal of Indoor and Seamless Positioning and Navigation","volume":"1 ","pages":"187-198"},"PeriodicalIF":0.0,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10329418","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138822152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Use of GNSS Doppler for Prediction in Kalman Filtering for Smartphone Positioning 在智能手机定位卡尔曼滤波中使用全球导航卫星系统多普勒进行预测

IEEE Journal of Indoor and Seamless Positioning and Navigation Pub Date : 2023-11-28 DOI: 10.1109/JISPIN.2023.3337188

Naman Agarwal;Kyle O'Keefe

引用次数: 0