The Affective Computing Study of Posture and Attention Recognition - An Example on The 3D School Guide System

碩士 === 國立臺中科技大學 === 資訊管理系碩士班 === 104 === The Affective Computing has changed the design thinking patterns of the Human-computer Interaction completely in recent years. In order to promote the intuitive and user-friendly on Human-Computer Interaction (HCI) system, there are more and more studies...

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Bibliographic Details
Main Authors: Cian-Huei Lin, 林千慧
Other Authors: Ming-Ni Wu
Format: Others
Language:zh-TW
Published: 2016
Online Access:http://ndltd.ncl.edu.tw/handle/dbu2xh
Description
Summary:碩士 === 國立臺中科技大學 === 資訊管理系碩士班 === 104 === The Affective Computing has changed the design thinking patterns of the Human-computer Interaction completely in recent years. In order to promote the intuitive and user-friendly on Human-Computer Interaction (HCI) system, there are more and more studies regard human emotions and behaviors as a key element in HCI, and try to introduce affective computing into system. Therefore, this study hopes to combine body movement and eyes gaze behavior into the system, and try to integrate emotion expression in posture and attention into the 3D School Guide System which developed on real campus. This study hope to analyze user’s body movement and gaze as the emotional judgment, and shows content feedback correspond to the areas and the emotions through the process of users are visiting the school environment. In this way, the operation burden can be reduced and user''s interactive experience can be improved to achieve intuitive and user-friendly experience. This study developed two different emotion operational modes, the operation of body emotion and attention emotion. In order to investigate whether to join the operation of emotional factors can improve the past interactive experience, keyboard operation and motion sensing operation were incorporated in comparison. The results in the overall interactive experience showed that most of the participants were satisfied with the operation modes which integrated emotion recognition, and not only reduced operating load significantly, but also thought that they are more interesting than the past operation modes. Finally, this study showed the limits of this study and improving policies for future studies.