gleisurfer

Making clearance outlining way easier!

Siemens
iOS
Machine Learning
AR

Makers

Meva Himmetoglu
Engineering
Doruk Cetin
Michael Chang

Technologies

Languages

Python
C++

SHORT DESCRIPTION

Gleisurfer is an iOS app that helps the railway workers get a no-fuss clearance outline and anomalous object detection using augmented reality and machine learning.

WHY?

The clearance outlining on the railroad tracks are hard to do manually with bulky spatial calliper. Today smartphones are collecting way more data than we need! We can use state-of-the-art point cloud generation, 3D reconstruction and segmentation methods to safely create the outline of the train clearance and detect if an object is not supposed to be there!

Repository

Check out our code and the output predictions for the demo provided here:

Features

Automatic Segmentation of Rail Tracks

We use Pytorch and BiSeNetv2 architecture to create the railway track segmentation from a video, or a real-time flow of frames.

Object Detection

We add on the capability of detecting objects using yolov5 model in the frame. If the object falls into a category that does not belong to be in the tracks, the user is notified.

3D Reconstruction

We rconstruct the 3D representation of a scene using structure from motion, and create meshes from the point cloud to further improve the analysis.

Real-time helper and more.

We ambition an iOS app where you can automatically place the train clearance outline and follow it along the tracks. The 3D reconstruction of the first run is further available in the app for the anomaly analysis and automatic detection.

Got some feedback or found a bug? Let us know on Discord