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" Smartphone-based indoor map construction : "
Ruipeng Gao, Fan Ye, Guojie Luo, Jason Cong.
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BL
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| Record Number
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889299
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| Main Entry
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Gao, Ruipeng
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| Title & Author
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Smartphone-based indoor map construction : : principles and applications /\ Ruipeng Gao, Fan Ye, Guojie Luo, Jason Cong.
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| Publication Statement
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Singapore :: Springer,, 2018.
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| Series Statement
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SpringerBriefs in computer science
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| Page. NO
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1 online resource
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| ISBN
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9789811083785
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: 9811083789
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9789811083778
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9811083770
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Includes bibliographical references.
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| Contents
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Intro; Preface; Contents; 1 Introduction of Indoor Map Construction; 1.1 Introduction; Reference; 2 Indoor Map Construction via Mobile Crowdsensing; 2.1 Introduction; 2.2 Design Overview; 2.3 Landmark Modeling; 2.3.1 The Landmark Model; 2.3.2 Coordinates of Geometric Vertices; 2.3.3 Connecting Points of Wall Segments; 2.3.4 Example; 2.4 Landmark Placement; 2.4.1 Notations; 2.4.2 Spatial Relation Acquisition; 2.4.3 Problem Formulation; 2.4.4 Optimization Algorithm; 2.5 Map Augmentation; 2.5.1 Wall Reconstruction; 2.5.2 Hallway Reconstruction; 2.5.3 Room Reconstruction.
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2.6 Connection Area Detection2.6.1 Types of Connection Areas; 2.6.2 Features; 2.6.3 Unsupervised Classification; 2.6.4 Refinement and Placement; 2.6.5 Types of Connection Areas; 2.7 Performance; 2.8 Discussion; 2.9 Related Work; 2.10 Conclusion; References; 3 Incremental Indoor Map Construction with a Single User; 3.1 Introduction; 3.2 Overview; 3.3 Localization via a Single Image; 3.4 Trajectory Calibration and Cleaning; 3.4.1 Trajectory Calibration; 3.4.2 Trajectory Cleaning; 3.5 Map Fusion Framework; 3.5.1 Dynamic Bayesian Network; 3.5.2 Particle Filter Algorithm; 3.6 Landmark Recognition.
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3.7 Compartment Estimation3.8 Performance; 3.9 Discussion; 3.10 Related Work; 3.11 Conclusion; References; 4 Indoor Localization by Photo-Taking of the Environment; 4.1 Introduction; 4.2 Relative Position Measurement; 4.3 Triangulation Method; 4.3.1 User Operations and Location Computation; 4.3.2 Criteria for Users to Choose Reference Objects; 4.3.3 Robustness of the Localization Primitive; 4.4 Site Survey for Reference Objects Coordinates; 4.4.1 Location Estimation in Unmapped Environments; 4.4.2 Experiments on Site Survey; 4.5 Identifying Chosen Reference Objects.
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4.5.1 System Architecture and Workflow4.6 Benchmark Selection of Reference Objects; 4.6.1 Benchmark Selection Problem; 4.6.2 NP-Completeness Proof; 4.6.3 A Heuristic Algorithm; 4.7 Improve Localization with Geographical Constraints; 4.7.1 Experiment Results and Problems in Early Prototype; 4.7.2 Geographical Constraints; 4.7.3 System Localization Performance; 4.8 Discussion; 4.9 Related Work; 4.10 Conclusion; References; 5 Smartphone-Based Real-Time Vehicle Tracking in Indoor Parking Structures; 5.1 Introduction; 5.2 Design Overview; 5.3 Trajectory Tracing; 5.3.1 Conventional Approaches.
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5.3.2 Shadow Trajectory Tracing5.3.3 Equivalence Proof; 5.4 Real-Time Tracking; 5.4.1 Intuition; 5.4.2 Road Skeleton Model; 5.4.3 Probabilistic Tracking Framework; 5.4.4 Tracking Algorithms; 5.5 Landmark Detection; 5.5.1 Types of Landmarks; 5.5.2 Feature and Classification Algorithm; 5.5.3 Prediction and Rollback; 5.6 Performance; 5.7 Discussion; 5.8 Related Work; 5.9 Conclusions; References.
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| Abstract
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This book focuses on ubiquitous indoor localization services, specifically addressing the issue of floor plans. It combines computer vision algorithms and mobile techniques to reconstruct complete and accurate floor plans to provide better location-based services for both humans and vehicles via commodity smartphones in indoor environments (e.g., a multi-layer shopping mall with underground parking structures). After a comprehensive review of scene reconstruction methods, it offers accurate geometric information for each landmark from images and acoustics, and derives the spatial relationships of the landmarks and rough sketches of accessible areas with inertial and WiFi data to reduce computing overheads. It then presents the authors' recent findings in detail, including the optimization and probabilistic formulations for more solid foundations and better robustness to combat errors, several new approaches to promote the current sporadic availability of indoor location-based services, and a holistic solution for floor plan reconstruction, indoor localization, tracking, and navigation. The novel approaches presented are designed for different types of indoor environments (e.g., shopping malls, office buildings and labs) and different users. A valuable resource for researchers and those in start-ups working in the field, it also provides supplementary material for students with mobile computing and networking backgrounds.
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| Subject
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Indoor positioning systems (Wireless localization)
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| Subject
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Indoor positioning systems (Wireless localization)
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TECHNOLOGY ENGINEERING-- Mechanical.
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| Dewey Classification
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621.3841/91
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| LC Classification
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TK5103.48323
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| Added Entry
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Cong, Jason
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Luo, Guojie
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Ye, Fan
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