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Photorealistic Learned Landscapes for Augmented Reality

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Published on: June 27, 2025

Mobile augmented reality based indoor map for improving geo-visualization.

Wei Ma¹, Shuai Zhang¹, Jincai Huang²

¹School of Civil Engineering, Chongqing Jiaotong University, Chongqing, Nanan, China.

Peerj. Computer Science

|October 4, 2021

Summary

This summary is machine-generated.

This study introduces a novel augmented reality (AR) system for indoor navigation. By fusing Bluetooth low energy (BLE) and pedestrian dead reckoning (PDR), it accurately overlays digital maps and information onto real-world views.

Keywords:

BLE and PDR fusion Geo-visualization Indoor localization Indoor map Mobile augmented reality

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Area of Science:

Geographic Information Systems (GIS)
Augmented Reality (AR)
Indoor Localization

Background:

Traditional AR-GIS applications struggle with local spatial information, leading to legibility issues and incomplete spatial relationships.
Indoor environments pose challenges for AR due to complex structures and lack of GPS, hindering location and semantic information display.

Purpose of the Study:

To develop an advanced AR-GIS system for accurate indoor spatial information display.
To overcome limitations of existing systems in detecting and presenting indoor location and semantic data.

Main Methods:

Implemented a multi-sensor fusion algorithm using a particle filter, combining Bluetooth low energy (BLE) and pedestrian dead reckoning (PDR) for camera position tracking.
Developed an algorithm to automatically register spatial information onto a live camera view based on phone orientation and position.
Extracted and matched indoor map bounding boxes to real-world scenes for accurate rendering of maps and semantic information.

Main Results:

Achieved an average positioning error of 1.47 meters.
Demonstrated that 80% of the method's positioning errors were within approximately 1.8 meters.
Validated the effective fusion of indoor spatial information with real-world scenes using AR.

Conclusions:

The proposed AR-GIS approach effectively links rich indoor spatial information to real-world environments.
This method shows promise for indoor navigation, crowdsourcing data collection, and indoor map reconstruction.