Indoor Localization
37 papers with code • 0 benchmarks • 5 datasets
Indoor localization is a fundamental problem in indoor location-based applications.
Benchmarks
These leaderboards are used to track progress in Indoor Localization
Libraries
Use these libraries to find Indoor Localization models and implementations
NILoc
RISEdb
dichasus-cf0x
Most implemented papers
Few-Shot Transfer Learning for Device-Free Fingerprinting Indoor Localization
BingJiaChen/few-shot-indoor-localization
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Device-free wireless indoor localization is an essential technology for the Internet of Things (IoT), and fingerprint-based methods are widely used.
MTLDesc: Looking Wider to Describe Better
Limited by the locality of convolutional neural networks, most existing local features description methods only learn local descriptors with local information and lack awareness of global and surrounding spatial context.
Neural Inertial Localization
This paper proposes the inertial localization problem, the task of estimating the absolute location from a sequence of inertial sensor measurements.
LASER: LAtent SpacE Rendering for 2D Visual Localization
LASER introduces the concept of latent space rendering, where 2D pose hypotheses on the floor map are directly rendered into a geometrically-structured latent space by aggregating viewing ray features.
D-InLoc++: Indoor Localization in Dynamic Environments
Lastly, we describe and improve the mistakes caused by gradient-based comparison between synthetic and query images and publish a new pipeline for simulation of environments with movable objects from the Matterport scans.
Indoor Localization with Robust Global Channel Charting: A Time-Distance-Based Approach
jeija/doppler-effect-channelcharting
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While CC has shown promising results in modelling the geometry of the radio environment, a deeper insight into CC for localization using multi-anchor large-bandwidth measurements is still pending.
The LuViRA Dataset: Synchronized Vision, Radio, and Audio Sensors for Indoor Localization
The dataset includes color images, corresponding depth maps, inertial measurement unit (IMU) readings, channel response between a 5G massive multiple-input and multiple-output (MIMO) testbed and user equipment, audio recorded by 12 microphones, and accurate six degrees of freedom (6DOF) pose ground truth of 0. 5 mm.
A Local Machine Learning Approach for Fingerprint-based Indoor Localization
The primary contribution of this paper is to introduce a novel local ML solution for indoor localization problems.
Constructing Metric-Semantic Maps using Floor Plan Priors for Long-Term Indoor Localization
We exploit 3D object detections from monocular RGB frames for both, the object-based map construction, and for globally localizing in the constructed map.
A Feasibility Study on Indoor Localization and Multi-person Tracking Using Sparsely Distributed Camera Network with Edge Computing
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 $1700m^2$, all while maintaining a strong focus on preserving privacy.
