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.
Keywords
MSC
65-D19
Cite this article
@article{cai-6018,
author = {Mengqi Du and Yue Zhang and Jianhua Zhang and Honghai Liu},
title = {Location Estimation from an Indoor Selfie},
journal = {Computing and Informatics},
volume = {42},
number = {5},
pages = {1213--1232},
year = {2023},
issn = {1335-9150},
doi = {10.31577/cai_2023_5_1213}
}
TY - JOUR AU - Mengqi Du AU - Yue Zhang AU - Jianhua Zhang AU - Honghai Liu TI - Location Estimation from an Indoor Selfie JO - Computing and Informatics VL - 42 IS - 5 SP - 1213 EP - 1232 PY - 2023 SN - 1335-9150 DO - 10.31577/cai_2023_5_1213 UR - https://doi.org/10.31577/cai_2023_5_1213 KW - Corneal imaging system KW - location estimation KW - privacy disclosure KW - selfie KW - social network ER -
Du, M., Zhang, Y., Zhang, J., & Liu, H. (2023). Location Estimation from an Indoor Selfie. Computing and Informatics, 42(5), 1213–1232. https://doi.org/10.31577/cai_2023_5_1213