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This paper presents a vision-based navigation system designed for indoor localization. The suggested framework works as a standalone 3 D 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 smartphones with relatively low energy consumption. Field experiments on Android smartphones show that the expected 3 D error is about 1–2 m in most real-life scenarios.

This paper presents a vision-based navigation system designed for indoor localization. The suggested framework works as a standalone 3 D 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 smartphones with relatively low energy consumption. Field experiments on Android smartphones show that the expected 3 D error is about 1–2 m in most real-life scenarios. [ABSTRACT FROM AUTHOR]