StEPS - Indoor visual navigation framework for mobile devices

This work presents a vision-based navigation system designed for Indoor localization. The suggested framework operates as a standalone 3D positioning system by fusing a sophisticated optical-flow pedometry with map-constrains using an advanced particle filter. The presented method requires no personal calibration and works on standard smart-phones with relatively low energy consumption. Preliminary field experiments on Android smart-phones show that the expected 3D error is about 1 − 2 meters in most real-life scenarios.