CHS: Small: Looking Across the Uncanny Valley: Procedural and Data-Driven Methods for Gaze Modeling

眼球运动在人类交流中起着关键作用，但它们仍然是人形动画的重要绊脚石。 计算机生成的化身目前缺乏真实的凝视，这会潜意识地分散观众的注意力，从而降低许多应用程序的有用性 其采用这些图形参与者（例如，教育/辅导/培训系统，包括动画代理），知觉问题，已被称为“恐怖谷。“该项目代表了两名具有互补技能的研究人员之间的合作，他们将通过开发化身的凝视动力学的整体模型来解决这个问题，该模型结合了详细的真实世界测量（在双目眼跟踪的帮助下）以及对眼睛运动和眼睛周围眼周皮肤区域的信号分析，以生成改进的合成眼动动画。 项目活动将包括创建一个注视运动数据库，感知实验，以提高我们对人类注视的不同组成部分的显着性的理解（眼球旋转、聚散、抖动、眼周皮肤运动）和它们在物理空间中的信号特性，和模范任务的执行（如阅读和对话）沿着一个软件工具，这将使动画师更容易设计令人信服的凝视在经常遇到的情况。 PI打算将本研究中开发的软件开源。 PI正在开发的凝视模型在以下方面与以前的方法不同。 第一，虽然其他人已经建模Cycloparta化身凝视很少访问稳定增长的眼动跟踪文献纳入双目眼球运动。 PI认为，三维物理空间中的双目眼动跟踪允许估计受试者在深度上注视的位置，从而记录、分析和建模凝视聚散度，这将产生更可信的特征。 第二，所提出的模型提供了一个微妙的凝视抖动的组成部分，这是动态现实主义的关键，因为眼睛从来没有完全静止。 第三，眼睛旋转的描述在数学上是简洁的，遵循生理规律，并且易于实现。 最后，所提出的建模工作包括感知研究，旨在调查每个模型组件的影响，并优化所得到的完整模型的参数。 程序模型是两个阶段，让人想起人类视觉的功能：眼睛旋转的自下而上的阶段，这将被用来表示凝视时，选择一系列的视点，其次是自上而下的阶段的凝视方向取决于一个给定的任务。 建立一个感知科学的基础凝视建模将促进合成演员的可信度，并将更广泛地影响不同的领域，如社会机器人，其中逼真的凝视模拟是创造可爱的机器人至关重要。

Eye movements play a key role in human communication, yet they remain a significant stumbling block for humanoid animation. Computer generated avatars currently lack realistic gaze, which subconsciously distracts viewers and thereby detracts from the usefulness of the many applications that employ these graphical actors (e.g., educational / tutoring / training systems that incorporate animated agents), a perceptual issue that has been dubbed the "uncanny valley." This project represents a collaboration between two investigators with complementary skills who will tackle the problem by developing a holistic model of gaze dynamics for avatars, which combines detailed real-world measurements (with the aid of binocular eye-tracking) and signal analysis of both eye motions and the periocular skin region around the eyes, to generate improved synthetic eye movement animations. Project activities will include creation of a database of gaze motions, perceptual experiments to improve our understanding of the saliency of different components of human gaze (eyeball rotation, vergence, jitter, periocular skin motion) and their signal properties in physical space, and the implementation of exemplary tasks (such as reading and conversations) along with a software tool which will enable animators to more easily design convincing gaze in frequently encountered situations. The PI intends to open-source the software to be developed in this research. The gaze model under development by the PI differs from previous approaches in the following ways. First, while others have modeled cyclopean avatar gaze few have accessed the steadily growing eye tracking literature for inclusion of binocular eye movement. The PI argues that binocular eye tracking in three-dimensional physical space allows estimation of where the subject is fixating in depth and, consequently, recording, analysis, and modeling of gaze vergence, which will yield more believable characters. Second, the proposed model provides a component of subtle gaze jitter, which is critical for dynamic realism as the eyes are never perfectly still. Third, the description of the rotations of the eyes is mathematically concise, follows physiological laws, and is easy to implement. Finally, the proposed modeling effort includes perceptual studies designed to investigate the influence of each model component and to optimize the parameters of the resulting complete model. The procedural model is two-staged and reminiscent of the functionality of human vision: a bottom-up stage of eye rotation, which will be used to represent gaze when selecting a series of look points, followed by a top-down stage of gaze orientation dependent on a given task. Building a perceptual science underlying gaze modeling will foster the believability of synthetic actors, and will more broadly impact diverse areas such as social robotics where realistic gaze simulation is crucial for creating likable robots.