Location Estimation from an Indoor Selfie

Authors

  • Mengqi Du College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China
  • Yue Zhang College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China
  • Jianhua Zhang School of Computer Science and Engineering, Tianjin University of Technology, Tianjin, China
  • Honghai Liu School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen, China

DOI:

https://doi.org/10.31577/cai_2023_5_1213

Keywords:

Corneal imaging system, location estimation, privacy disclosure, selfie, social network

Abstract

With the development of social networks and hardware devices, many young people have post a lot of high definition v-logs containing selfie images and videos to commemorate and share their daily lives. We found that the reflected image of corneal position in the high definition selfie image has been able to reflect the position and posture of the selfie taker. The classic localization works estimating the position and posture from a selfie are difficult because they lack the knowledge of the environment. The corneal reflection images inherently carry information about the surrounding environment, which can reveal the location, posture and even height of the selfie taker. We analyze the corneal reflection imaging process in the selfie scenario and design a validation experiment based on this process to estimate the pose of the selfie in several scenarios to further evaluate the leakage of the pose information of the selfie taker.

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Published

2024-01-31

How to Cite

Du, M., Zhang, Y., Zhang, J., & Liu, H. (2024). Location Estimation from an Indoor Selfie. Computing and Informatics, 42(5), 1213–1232. https://doi.org/10.31577/cai_2023_5_1213