USING MACHINE LEARNING TO ESCAPE THE UNCANNY VALLEY

使用机器学习逃离恐怖谷

• 批准号: 2739284
• 金额: --
• 依托单位: University of York
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2739284
• 关键词: USING; MACHINE; LEARNING; ESCAPE; UNCANNY

With the rise of digital art, Uncanny Valley has emerged from an esoteric robotics concept into an infectious memetic phenomenon, with specific memes such as 'Uncanny/Canny Mr. Incredible', or more generally uncanny faces being used as reaction images for humor. Critics and players will now refer to specific media being 'Uncanny' rather than using more general words as 'off-putting', demonstrating uncanniness cementing itself in the public consciousness as examples increasingly abound; ergo digital artists should be aware of evoking the uncanny even with modern rendering technology, as audiences become increasingly discerning of the Uncanny. This is most pertinent in videogames, where rendering is performed in real-time, meaning rendering constraints must be implemented. This potentially confines characters to the Uncanny Valley, as it may not be possible to increase graphical fidelity, thus artists may be left to either accept the uncanny or demaster their work (both undesirable options). This project aims to learn about the Uncanny Valley pertaining to modern skin rendering techniques, using artificial intelligence (specifically GANs) to directly map skin rendering parameters onto user assessments of uncanniness and realism. This can then be reverse engineered to provide automated tools for generatively rendering realistic non-uncanny skin, and predicting audience responses to skin realism, expediting QA testing. The primary experimental stage is to generate a face database with photorealistic skin to be assessed using psychometrics by participants. This is additionally one of few studies looking into the novel phenomena of training AI's to generate human-oriented psychologically salient content.

随着数字艺术的兴起，恐怖谷已经从一个深奥的机器人概念变成了一种具有感染力的模因现象，有一些特定的模因，比如“不可思议/不可思议先生”，或者更普遍的不可思议的脸被用作幽默的反应图像。评论家和玩家现在会将特定的媒体称为“不可思议”，而不是使用更一般的词“令人反感”，这表明不可思议在公众意识中不断巩固，这样的例子越来越多；因此，数字艺术家应该意识到，即使使用现代渲染技术，也要唤起不可思议的感觉，因为观众对不可思议的感觉越来越敏锐。这与电子游戏最为相关，因为渲染是实时执行的，这意味着必须执行渲染约束。这可能会将角色限制在恐怖谷中，因为这可能无法提高图像保真度，因此美术师可能会选择接受恐怖或精通他们的作品（这两种选择都是不可取的）。该项目旨在了解与现代皮肤渲染技术相关的恐怖谷，使用人工智能（特别是gan）直接将皮肤渲染参数映射到用户对恐怖和现实主义的评估上。然后，这可以逆向工程，以提供自动工具，生成逼真的非不可思议的皮肤，并预测用户对皮肤真实感的反应，加快QA测试。主要的实验阶段是生成一个具有逼真皮肤的面部数据库，供参与者使用心理测量学进行评估。这也是少数研究训练人工智能生成以人为导向的心理突出内容的新现象之一。