Arousal Evaluation of VR Affective Scenes Based on HR and SAM
PubDate: July 2019
Teams: South China University of Technology
Writers: Dan Liao; Wenzhuo Zhang; Guodong Liang; Yingxuan Li; Jingyan Xie; Lingqing Zhu; Xiangmin Xu; Lin Shu
Various of methods have been proposed for emotional induction including affective pictures, audios, and video clips. However, significant limitations have been exhibited such as low emotion elicitation efficiency and high susceptibility to ambient interferences. Considering virtual reality (VR) provides a more immersive and authentic audio-visual sense, this paper puts forward an emotion elicitation system using VR named Affective Virtual Reality System (AVRS). Firstly, the emotional multi-features were extracted and classified from the existing standard affective systems. Then the VR scenes were designed by writing scripts, building 3D modeling and scenes using Unreal Engine 4.12. Through Self-Assessment Manikin (SAM) evaluation, it was verified that the emotions inducted by the VR scenes were evenly distributed in the three-dimensional space of emotion, which reached the standardization of affective system in field of psychology. Then we further validated the advantages of AVRS by putting the four VR scenes into the LCD and VR device respectively. We tested the arousal level with the heart rate data and the SAM scale. The result shows that the arousal of other scenes have no significant difference from the videos in the VR environment, except the fear scene. We found that there are some conditions for the VR scenes to achieve a good emotional effect. Enhancing the interactivity and plot design is an important aspect.