• Science of Emotion and Sensibility
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• v.13 no.1
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• pp.197-206
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• 2010

For an emotion retrieval system implementation to support pedestrian navigation, coordinating the pedestrian emotion model with the system user's emotion is considered a key component. This study proposes a new method for capturing the user's model that corresponds to the pedestrian emotion model and examines the validity of the method. In the first phase, a database comprising a set of interior images that represent hypothetical destinations was developed. In the second phase, 10 subjects were recruited and asked to evaluate on navigation and satisfaction toward each interior image in five rounds of navigation experiments. In the last phase, the subjects' feedback data was used for of the pedestrian emotion model, which is called ‘learning' in this study. After evaluations by the subjects, the learning effect was analyzed by the following aspects: recall ratio, precision ratio, retrieval ranking, and satisfaction. Findings of the analysis verify that all four aspects significantly were improved after the learning. This study demonstrates the effectiveness of the learning algorithm for the proposed pedestrian emotion model. Furthermore, this study demonstrates the potential of such pedestrian emotion model to be well applicable in the development of various mobile contents service systems dealing with visual images such as commercial interiors in the future.

• Archives of design research
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• v.20 no.3 s.71
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• pp.203-214
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• 2007

This study proposes an information retrieval method reflecting the user's preferences based on the fuzzy set theory to develop information contents which support pedestrian's navigation. Firstly, the research evaluated subjects' preferences on commercial spaces set to a hypothetical destination. Also it surveyed the causal relationship between the visual characteristics and the emotional characteristics to propose methods of Navigation Knowledge Base (NKB). The NKB was composed of three elements; 1. the correlation model between emotional characteristics, 2. the causal relationship between visual characteristics and emotional characteristics, 3. the transformation model between visual characteristics and the physical characteristics. Secondly, this study classified the pedestrian's destination search into 4 types with his or her preferences and the time conditions limited during navigation. For each type it presented the Destination Search Algorithm (DSA). Finally, the research simulated the destination search in 4 navigation types using NKB and DSA and verified the availability of the information retrieval method reflecting pedestrian's preferences. In conclusion, the proposed information search method will be applied to reflect the user's preferences to develop information appliances.