View Proposal

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Proposer

Phil Bartie

Title

Indoor Positioning using Computer Vision

Goal

The goal is to find a user's position within a building by using a camera to check the ceiling

Description

GNSS (eg GPS) is a wonderful solution for positioning a device outside. However indoors tracking is much more difficult given the obfuscation of the roof and building materials between the receiver and satellites. There are a number of options for indoor positioning including WiFi fingerprinting, setting up bluetooth beacons, IMU (e.g. foot tracking). There are also solutions based on VPS (visual positioning systems) which use the camera and computer vision to locate the user from a library of previoiusly captured images. This project will develop a simple mobile client which sends image updates from the front camera of a phone held looking upwards to a server. The server will carry out comparisons looking for correspondences within a library of previously captured images. The result would be being able to give a location back to the user which locates them on an indoor map. The project will involve computer vision (eg OpenCV, scikit-image) and development of a web app that takes a camera feed from a mobile device. For this project we particularly want to focus on how well tracking a ceiling will work for positioning around indoor spaces (eg university buildings).

Resources

Mobile device, server

Background

Interest to learn OpenCV / scikit-image / PILLOW

Url

Difficulty Level

Moderate

Ethical Approval

InterfaceOnly

Number Of Students

1

Supervisor

Phil Bartie

Keywords

Degrees

Bachelor of Science in Computer Science
Bachelor of Science in Computer Systems
Master of Engineering in Software Engineering
Master of Science in Data Science
Master of Science in Robotics