AN INSTANCE-BASED SCORING SYSTEM FOR INDOOR LANDMARK SALIENCE EVALUATION
| Authors | |
|---|---|
| Year of publication | 2018 |
| Type | Article in Proceedings |
| Conference | 7TH INTERNATIONAL CONFERENCE ON CARTOGRAPHY AND GIS, VOLS 1 AND 2 |
| MU Faculty or unit | |
| Citation | |
| web | https://iccgis2018.cartography-gis.com/7ICCGIS_Proceedings/7_ICCGIS_2018%20(44).pdf |
| Keywords | Landmark; Indoor Landmark; Landmark salience; Scoring system |
| Description | Landmarks are the clues which connect the cartographic space, the real-world space and the cognitive map space and they play an important role in the spatial information expression and transmission. Landmarks can help users to establish a structured understanding of the environment as "anchor point" which have a significant contrast to the surroundings so that users do not need extra effort to recognize them because of its own salience. Landmark salience evaluation is the basis for users to select landmarks. However, evaluation methods for outdoor landmark salience cannot fully adapt to the indoor environment and these methods often rely on detailed data about every spatial object which is difficult to obtain easily. Some research has developed a heuristic scoring system to make the evaluation easier, but these methods are always category-based so the accuracy is limited due to the few categories of indoor landmarks. The uniqueness and location of a single landmark are important, the traditional five point rating is obscure for some specific indicators and the weight calculation method is needed to be clearer. In this paper, we introduce an instance-based scoring system as an evaluation model for indoor landmark salience. The feasibility of this method is demonstrated by a case study in the Dongchenghui shopping mall near Nanjing Normal University (Nanjing, China). The result shows that the landmark salience evaluated by this method has a strong correlation with the subjects’ opinion. With landmark salience, landmark representation in indoor map can reflect the knowledge of indoor space at different levels helping users to complete their wayfinding task more comfortable. |
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