Design of vision-based indoor positioning based on embedded system

Tsung Han Tsai, Chih Hao Chang, Shih Wei Chen, Chia Hsiang Yao

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


Indoor positioning techniques have become very important in recent years. Due to the wide deployment of surveillance cameras, it has become feasible to use the videos for indoor positioning. The success of using this approach can also reduce the load of security persons of watching the monitors all the time. In this study, the authors propose a vision-based indoor positioning system. The proposed method uses a frame processing technique and applies the Gaussian mixture learning for video background model. The foreground object can be extracted by using the background subtraction. Based on the foreground object, the objects can be tracked and used in the direct linear transform, and generate a bird's-eye map with camera information. A real-time demonstration has been also provided. It shows the tracing of the moving objects and the bird's-eye view.

Original languageEnglish
Pages (from-to)423-430
Number of pages8
JournalIET Image Processing
Issue number3
StatePublished - 28 Feb 2020


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