The performance of outdoor positioning has become excellent with the emergence of Global Positioning System (GPS), but GPS is not reliable indoors. The ability of a system to perform indoor positioning without GPS is still challenging and has gained a lot of attention in recent years. Despite a lot of research effort, existing indoor positioning systems based on different technologies are still limited because most of them either require expensive infrastructure (ultrasound), or limited coverage (Bluetooth) or provide low accuracy (audible sound). On the other hand, computer vision offers a good cost effective solution for indoor positioning due to the use of cheap cameras.
In this talk, I will first discuss the requirements of indoor and outdoor navigation systems followed by a quick overview of some well known travel aids, which are in use by blind people. I will then present our vision based indoor positioning algorithm along with experimental results.
This talk provides a summary of my PhD work.
Last modified: Tuesday, 17-Sep-2013 08:54:54 NZST
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