Publication: Familiarity-dependent computational modelling of indoor landmark selection for route communication: a ranking approach
Familiarity-dependent computational modelling of indoor landmark selection for route communication: a ranking approach
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Zhou, Z., Weibel, R., & Huang, H. (2022). Familiarity-dependent computational modelling of indoor landmark selection for route communication: a ranking approach. International Journal of Geographical Information Science, 36(3), 514–546. https://doi.org/10.1080/13658816.2021.1946542
Abstract
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Landmarks play key roles in human wayfinding and mobile navigation systems. Existing computational landmark selection models mainly focus on outdoor environments, and aim to identify suitable landmarks for guiding users who are unfamiliar with a particular environment, and fail to consider familiar users. This study proposes a familiarity-dependent computational method for selecting suitable landmarks for communicating with familiar and unfamiliar users in indoor environments. A series of salience measures are proposed to quantify the
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- Zhou, Zhiyong
- Weibel, Robert
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Zhou, Z., Weibel, R., & Huang, H. (2022). Familiarity-dependent computational modelling of indoor landmark selection for route communication: a ranking approach. International Journal of Geographical Information Science, 36(3), 514–546. https://doi.org/10.1080/13658816.2021.1946542
