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A Spatial Division Clustering Method and Low Dimensional Feature Extraction Technique Based Indoor Positioning System
2014
Sensors
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In terms of fine localization, based on the Kernel Principal Component Analysis method, the proposed positioning system outperforms its counterparts based on other feature extraction methods in low dimensionality ...
To solve these issues, in this paper we propose a positioning system based on the Spatial Division Clustering (SDC) method for clustering the fingerprint dataset subject to physical distance constraints ...
In sum, the Kernel PCA algorithm deployed in the proposed indoor positioning system is more capable of extracting the features of RSS with low dimensionality in an office environment, its robustness and ...
doi:10.3390/s140101850
pmid:24451470
pmcid:PMC3926643
fatcat:3hbunoppprfg7p5uxinrre4rq4
A Survey of Machine Learning for Indoor Positioning
2020
IEEE Access
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In fingerprint-method clustering is performed based on these extracted features. Feature extraction is also important for NLOS identification and mitigation. ...
The fingerprinting position method based on RSSI measurement can be used for RFID-based indoor positioning systems [65] . ...
doi:10.1109/access.2020.3039271
fatcat:htzgf2mwp5gmjbx3cczg5rl7ru
Indoor versus outdoor scene recognition for navigation of a micro aerial vehicle using spatial color gist wavelet descriptors
2019
Visual Computing for Industry, Biomedicine, and Art
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A binary and multiclass support vector machine (SVM) classifier with linear and non-linear kernels was used to classify indoor versus outdoor scenes and indoor scenes, respectively. ...
In this paper, we have also discussed the feature extraction methodology of several, state-of-the-art visual descriptors, and four proposed visual descriptors (Ohta color-GIST descriptors, Ohta color-GIST ...
Availability of data and materials The datasets used and/or analyzed for indoor versus outdoor scene categorization and indoor scene categorization are available from the corresponding author on reasonable ...
doi:10.1186/s42492-019-0030-9
pmid:32240408
fatcat:5ik3pd24izf7toiio343kcu72m
Indoor positioning and wayfinding systems: a survey
2020
Human-Centric Computing and Information Sciences
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In particular, the paper reviews different computer vision-based indoor navigation and positioning systems along with indoor scene recognition methods that can aid the indoor navigation. ...
The article concludes with a brief insight into future directions in indoor positioning and navigation systems. ...
Compared to 2-dimensional image feature based approaches 3-dimensional features and RGB-D image-based methods are more reliable for indoor navigation. ...
doi:10.1186/s13673-020-00222-0
fatcat:m7lt5zdcjbbsvlh7fwatjvpx6y
Machine Learning Based Indoor Localization Using Wi-Fi RSSI Fingerprints: An Overview
2021
IEEE Access
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To provide good direction for future research, we discuss the current challenges and potential solutions related to ML-based indoor localization systems. ...
Based on various practical issues related to large delays, high design cost, and limited performance, conventional localization techniques are not practical for indoor IoT applications. ...
However, LDA is not applicable for nonlinear applications [130] .
6) t-SNE t-SNE is a nonlinear, unsupervised, and manifold-based feature extraction method that maps high-dimensional data to low-dimensional ...
doi:10.1109/access.2021.3111083
fatcat:7o6zb7kycrgftfpsukuwnsl24m
Extended Spectral Regression for efficient scene recognition
2014
Pattern Recognition
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In the ESR-based scene recognition, we first propose an enhanced lowlevel feature representation which combines the scale, orientation, spatial position, and local appearance of a local feature. ...
Then, an efficient Bag-of-Words (BOW) based method is developed which employs ESR to encapsulate local visual features with their semantic, spatial, scale, and orientation information for scene recognition ...
, spatial position, and visual appearance of a local feature. ...
doi:10.1016/j.patcog.2014.03.012
fatcat:qmywq66dsbg5hknv5jgximwnqe
A Survey of Recent Indoor Localization Scenarios and Methodologies
2021
Sensors
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The key localization techniques like RSSI-based fingerprinting technique are presented using supervised machine learning methods, namely SVM (support vector machine), KNN (K nearest neighbors) and NN ( ...
In this survey, a large number of existing techniques are presented for different indoor network structures and channel conditions, divided as LOS (light-of-sight) and NLOS (non light-of-sight). ...
The program is cofinanced by the Normandy Region and the European Union. Europe is committed in Normandy with the European Regional Development Fund (ERDF). ...
doi:10.3390/s21238086
pmid:34884090
fatcat:juacgglap5f5jaezn3w2lrur3u
A State-of-the-Art Survey on Multidimensional Scaling Based Localization Techniques
2019
IEEE Communications Surveys and Tutorials
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Generally, the most popular localization/positioning system is the global positioning system (GPS). GPS works well for outdoor environments but fails in indoor and harsh environments. ...
In this paper, a comprehensive survey is presented for MDS and MDS-based localization techniques in WSNs, IoT, cognitive radio networks, and 5G networks. ...
All of the above mentioned indoor positioning systems are based on a specific ranging technique. ...
doi:10.1109/comst.2019.2921972
fatcat:5vaody5gybfproeakhrr5ch4eu
3-D Data Models
[chapter]
2017
Encyclopedia of GIS
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Synonyms 3D data clustering; 3D Geo-DBMS; 3D spatial indexing; Access method; Urban data management; Vector quantization ...
Acknowledgements This study was supported by TUBITAK-The Scientific and Technological Research Council of Turkey research grant [grant number: 112Y050]. ...
Grid-Based Algorithms Grid-based algorithm is the clustering technique that quantizes a space or region into a finite number of cells. ...
doi:10.1007/978-3-319-17885-1_100004
fatcat:6o75kluwh5dknle7cvmgmnsnja
Intelligent image classification-based on spatial weighted histograms of concentric circles
2018
Computer Science and Information Systems
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However, SPM is not rotation-invariant and does not allow a change in pose and view point, and it represents the image in a very high dimensional space. ...
Spatial Pyramid Matching (SPM) is a popular technique that computes the spatial layout of the 2-D image space. ...
Clustering reduces the high dimensional feature space; hence as a result of clustering, each descriptor is mapped to a visual word and the final representation of the image is the histogram of visual words ...
doi:10.2298/csis180105025z
fatcat:gqfhh3xxavf3bad4t44p3ujcjm
3D Models
[chapter]
2017
Encyclopedia of GIS
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Synonyms 3D data clustering; 3D Geo-DBMS; 3D spatial indexing; Access method; Urban data management; Vector quantization ...
Acknowledgements This study was supported by TUBITAK-The Scientific and Technological Research Council of Turkey research grant [grant number: 112Y050]. ...
Grid-Based Algorithms Grid-based algorithm is the clustering technique that quantizes a space or region into a finite number of cells. ...
doi:10.1007/978-3-319-17885-1_100007
fatcat:n7jatghxh5filenbpkconn44hu
A State-of-the-Art Survey on Multidimensional Scaling Based Localization Techniques
[article]
2019
arXiv
pre-print
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Generally, the most popular localization/ positioning system is the Global Positioning System (GPS). GPS works well for outdoor environments but fails in indoor and harsh environments. ...
In this paper, a comprehensive survey is presented for MDS and MDS based localization techniques in WSNs, Internet of Things (IoT), cognitive radio networks, and 5G networks. ...
All of the above mentioned indoor positioning systems are based on a specific ranging technique. ...
arXiv:1906.03585v1
fatcat:n2erdwcivfgflncbrunexyidwi
Interoperability, XML Schema
[chapter]
2017
Encyclopedia of GIS
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Geospatial Semantic Integration Geospatial Semantic Web Geospatial Semantic Web: Applications Geospatial Semantic Web, Interoperability Geospatial Semantic Web: Personalization Indexing, Hilbert R-Tree, Spatial ...
The intelligence extraction step is performed by image interpreters through spectral and object-based classification techniques as well as varying forms of automated and manual feature extraction methods ...
It offers a standard way to encode spatial features, feature properties, feature geometries, and the location of the feature geometries based on a standard data model. ...
doi:10.1007/978-3-319-17885-1_100625
fatcat:bgxdhdxa4bewzcggrogz56rdpi
2D/3D Sensor Exploitation and Fusion for Enhanced Object Detection
2014
2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops
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This paper describes a method for object (e.g., vehicles, pedestrians) detection and recognition using a combination of 2D and 3D sensor data. ...
., clusters of 3D points) containing potential objects are extracted from the corresponding input point cloud in an unsupervised manner. ...
Most of the existing clustering methods rely on spatial decomposition techniques that find subdivisions and boundaries to allow the data to be grouped together based on a measure of "proximity. ...
doi:10.1109/cvprw.2014.119
dblp:conf/cvpr/XuKZCO14
fatcat:enczztlksnd6vbwmmnbohp3zfi
Scene search based on the adapted triangular regions and soft clustering to improve the effectiveness of the visual-bag-of-words model
2018
EURASIP Journal on Image and Video Processing
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This article presents a novel adapted triangular area-based technique, which computes local intensity order pattern (LIOP) features, weighted soft codebooks, and triangular histograms from the four triangular ...
The position of an object within an image is obtained by analyzing the content-based properties like shape, texture, and color, while compositional properties present the image layout and include the photographic ...
., patch-level and image-level, are employed for feature fusion. For compact representation of high-dimensional feature vector, clustering technique based on k-means is used to formulate a codebook. ...
doi:10.1186/s13640-018-0285-7
fatcat:pnmnmssgkjdhxmmu4cmffst65i
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