Deep combining of local phase quantization and histogram of oriented gradients for indoor positioning based on smartphone camera

Jichao Jiao and Zhongliang Deng

International Journal of Distributed Sensor Networks, 2017, vol. 13, issue 1, 1550147716686978

Abstract: To achieve high accuracy in indoor positioning using a smartphone, there are two limitations: (1) limited computational and memory resources of the smartphone and (2) the human walking in large buildings. To address these issues, we propose a new feature descriptor by deeply combining histogram of oriented gradients and local phase quantization. This feature is a local phase quantization of a salient histogram of oriented gradient visualizing image, which is robust in indoor scenarios. Moreover, we introduce a base station–based indoor positioning system for assisting to reduce the image matching at runtime. The experimental results show that accurate and efficient indoor location positioning is achieved.

Keywords: Indoor positioning; smartphone; salient region detection; deep combining of histogram of oriented gradients and local phase quantization; histogram of oriented gradient visualization (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:13:y:2017:i:1:p:1550147716686978

DOI: 10.1177/1550147716686978

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