• Science of Emotion and Sensibility
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• v.17 no.1
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• pp.39-52
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• 2014

Use of vision and audition for video reality has made much advancement. However use of olfaction, which is effective in inducing emotion, has not yet been realized due to technical limitations and lack of basic research. In particular it is difficult to fabricate many odors required for each different video. One way to resolve this is to discover clusters of odors of similar smell and to use representative odor for each cluster. This research explored clusters of odors based on pairwise similarity ratings. 300 diverse odors were first collected and sorted them into 11 categories. We selected 152 odors based on their frequency, preference, and concreteness. Participants rated similarity on 1,018 pairs of odors from selected odors and the results were analyzed using multi-dimensional scaling (MDS). Based on the idea that low odor concreteness would support valid use of representative odor, the MDS results are presented from low to high smell concreteness. First, flowers, plants, fruits, and vegetables was classified under the easy categories to use representative odor due to their low smell concreteness (Figure 1). Second, chemicals, personal cares, physiological odors, and ordinary places was classified under the careful categories of using it due to their intermediate concreteness (Figure 2). Finally, food ingredients, beverages, and foods was classified under the difficult categories to use it because of their high concreteness (Figure 3). The results of this research will contribute to reduction of cost and time in odor production and provision of realistic media service to customers at reasonable price.

• Journal of the HCI Society of Korea
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• v.8 no.2
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• pp.9-19
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• 2013

There has been much advancement in reality enhancement using audio-visual information. On the other hand, there is little research on provision of olfactory information because smell is difficult to implement and control. In order to obtain necessary basic data when intend to provide smell for video reality, in this research, we investigated user perception of smell in diverse videos and then classified the videos based on the collected user perception data. To do so, we chose five main questions which were 'whether smell is present in the video'(smell presence), 'whether one desire to experience the smell with the video'(preference for smell presence with the video), 'whether one likes the smell itself'(preference for the smell itself), 'desired smell intensity if it is presented with the video'(smell intensity), and 'the degree of smell concreteness'(smell concreteness). After sampling video clips of various genre which are likely to receive either high and low ratings in the questions, we had participants watch each video after which they provided ratings on 7-point scale for the above five questions. Using the rating data for each video clips, we constructed scatter plots by pairing the five questions and representing the rating scale of each paired questions as X-Y axes in 2 dimensional spaces. The video clusters and distributional shape in the scatter plots would provide important insight into characteristics of each video clusters and about how to present olfactory information for video reality.