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Emotions Appraisal with Face Reading in a Touristic Virtual Environment Prototype

机译:情感评估在旅游虚拟环境原型中脸部读数

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User engagement is an essential condition for assessing the quality of an interactive experience. Nowadays, the tourism industry has been using experiences based on interactive proposals to involving users. However, tourism industry needs more effective strategies in the dissemination of the cultural contents, whether material or immaterial, and in particular in emerging countries such as the Sao Tome and Principe Islands. In this context, how can the tourism industry offer contents capable to provide levels of engagement able to attract potential tourists to visit these tourist spots. And so, the development of immersive proposals in a virtual environment, can play an important role to engage potential tourists. In this context, this article has as primary goal the evaluating how 3D environments and interaction strategy can influence the emotional reactions of potential users of this product. In particular, we want to know if this virtual environment is capable of involving participants and provide interactive experiences capable to seducing and arousing interest in the islands. This evaluation was made using the Face-Reading tool, Self-Assessment-Mannequin(SAM)and Geneva Emotion wheel(GEW). The data collection tools used(Face-Reading, SAM and GEW)allowed to identify differences between the different moments of the game interaction, and they also presented similar results. In conclusion, Face-Reading achieves a level of continuous discrimination of the user experience, particularly in relation to engagement, allowing a better identification of the moments associated with the emotional reactions.
机译:用户参与是评估互动体验质量的重要条件。如今,旅游业一直在利用基于互动建议来涉及用户的经验。然而,旅游业在传播文化内容方面需要更有效的策略,无论是物质还是无关紧要,特别是在新兴国家,如圣多美和普林西比群岛。在这种情况下,旅游业如何提供能够提供能够吸引潜在游客访问这些旅游景点的参与水平的内容。因此,在虚拟环境中的沉浸式提案的发展可以发挥重要作用来吸引潜在的游客。在这种情况下,本文具有主要目标,评估3D环境和交互策略如何影响本产品的潜在用户的情绪反应。特别是,我们想知道这个虚拟环境是否能够涉及参与者并提供能够诱惑和唤起对岛屿兴趣的互动体验。这种评估是使用面部阅读工具,自我评估 - 时装模特(SAM)和日内瓦情感轮(铸造)进行的。使用的数据收集工具(面对面读取,SAM和GEW)允许识别游戏交互的不同时刻之间的差异,并且它们也呈现了类似的结果。总之,面部读数达到用户体验的连续辨别水平,特别是与参与关系,允许更好地识别与情绪反应相关的瞬间。

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