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

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  • Jichao Jiao
  • Zhongliang Deng

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.

Suggested Citation

  • Jichao Jiao & Zhongliang Deng, 2017. "Deep combining of local phase quantization and histogram of oriented gradients for indoor positioning based on smartphone camera," International Journal of Distributed Sensor Networks, , vol. 13(1), pages 15501477166, January.
    • Handle: RePEc:sae:intdis:v:13:y:2017:i:1:p:1550147716686978
    DOI: 10.1177/1550147716686978
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