论文标题
人格驱动的目光动画，具有条件生成对抗网络
Personality-Driven Gaze Animation with Conditional Generative Adversarial Networks
论文作者
论文摘要
我们提出了一种生成的对抗学习方法，以综合给定个性的凝视行为。我们使用现有数据集训练该模型，该数据集包括42名参与者执行日常任务的数据和人格特质。鉴于大五个人格特征的值（开放性，尽职尽责，外向，愉快和神经质），我们的模型产生了由凝视目标，眨眼时间和瞳孔维度组成的时间序列数据。我们使用生成的数据来合成虚拟代理在游戏引擎上的注视运动。
We present a generative adversarial learning approach to synthesize gaze behavior of a given personality. We train the model using an existing data set that comprises eye-tracking data and personality traits of 42 participants performing an everyday task. Given the values of Big-Five personality traits (openness, conscientiousness, extroversion, agreeableness, and neuroticism), our model generates time series data consisting of gaze target, blinking times, and pupil dimensions. We use the generated data to synthesize the gaze motion of virtual agents on a game engine.
