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Experience Surveillance Suite for Unity 3D

机译:体验Unity 3D监控套件

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摘要

Monitoring the emotional state of players in games can get quite complex, taking into consideration that the game context affects the player and that a game may contain various emotional features. Furthermore, since the experience of playing a game occurs unconsciously, methods such as think aloud may interrupt the playing experience. Other methods include fitting cables and electrodes to the player in order to monitor measurements such as heart rate. Although such devices can offer significant results, they are not commonly found and may cause discomfort. In this project we propose a webcam-based heart rate monitoring method that can be used to predict the player's emotional state. The first objective was to analyze the heart rate changes with respect to the players' emotional state. The evaluation resulted in positive results, where the heart rate showed correlation with the following emotional states; frustration, fun, challenge and boredom. The second objective was to create a webcam-based method to monitor the heart rate. This was performed by extracting the RGB channels from the face region and then retrieving the underlying components using a dimensionality reduction method. Although the results obtained from the webcam-based method were not ideal, this was expected taking into consideration that the method was tested under realistic scenarios. The last objective was to predict the player's emotional state using the heart rate obtained from the webcam-based method. The accuracy of the prediction was up to 76%, which exceeds the aim of the project. Finally, by using the evaluation results it was possible to define a set of approaches on how this project can be extended by future researchers.
机译:考虑到游戏环境会影响玩家并且游戏可能包含各种情感特征,因此监视游戏中玩家的情绪状态可能会变得非常复杂。此外,由于玩游戏的体验是无意识的,所以大声思考的方法可能会打断玩游戏的体验。其他方法包括将电缆和电极安装到播放器上,以监视诸如心率之类的测量结果。尽管此类设备可以提供显着的结果,但并不常见,并且可能会引起不适。在此项目中,我们提出了一种基于网络摄像头的心率监测方法,该方法可用于预测玩家的情绪状态。第一个目标是分析与玩家情绪状态有关的心率变化。评估结果为阳性,其中心率与以下情绪状态相关。挫折,乐趣,挑战和无聊。第二个目标是创建一种基于网络摄像头的方法来监视心率。这是通过从面部区域提取RGB通道,然后使用降维方法检索基础成分来执行的。尽管从基于网络摄像头的方法获得的结果并不理想,但是考虑到该方法是在实际场景下进行测试的,因此可以预期。最后一个目标是使用从基于网络摄像头的方法中获得的心率来预测玩家的情绪状态。预测的准确性高达76%,超出了项目的目标。最后,通过使用评估结果,可以定义一套有关未来研究人员如何扩展该项目的方法。

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