Computational Colour Approach to Digital Imaging, Human Perception, Computer Vision and AR/VR/MR

数字成像、人类感知、计算机视觉和 AR/VR/MR 的计算色彩方法

• 批准号: RGPIN-2019-04255
• 负责人: Funt, Brian
• 金额: $ 2.04万
• 依托单位: Simon Fraser University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=750557
• 关键词: Computational; Colour; Approach; Digital; Imaging

Computational Colour Approach to Digital Imaging, Human Perception, Computer Vision and AR/VR/MR This proposal is about how the colours of objects are perceived by different `observers'-different people, different cameras-and under different lights (daylight, LED, fluorescent, tungsten). Colour is a very interdisciplinary field touching on psychology, philosophy, chemistry, physics, and computer science. My approach to understanding colour is to view colour perception as a computational process. As such, the models of colour perception developed in my laboratory are formulated as algorithms that can be tested both in terms of whether or not they simply provide the expected results, and secondly in terms of whether they operate in a way that is congruent with what is known about human colour perception from the psychophysical experiments conducted by psychologists. The fundamental difficulty in understanding and modeling colour perception is that because humans have only 3 types of colour-sensitive cones there is no one-to-one correspondence between the wavelengths of light entering the eye and perceived colour. There are many other difficulties too, such as how the same reflected-light spectrum may look different in different contexts, and these all contribute to colour being a fascinating field of research. These difficulties, however, present problems for the digital camera industry, the digital printing industry, the digital display industry, the textile industry, the lighting industry, the scientific use of colour (e.g., in medical applications), the digital preservation of artwork, and most recently to colour accuracy in augmented/mixed reality applications. The research projects in this proposal address fundamental issues of colour science that have direct application to all these technology areas. The objectives of the proposed research build on the recent progress in my laboratory that include work on metamerism, colour constancy and the limits thereof, establishing the set of all theoretically-possible colours, evaluating the colour rendering properties of lights, and evaluating the colour accuracy of digital cameras. The proposed objectives include: (i) a new illuminant-invariant approach to object classification and recognition with implications for machine learning generally; (ii) building a dataset with accurate ground truth of multispectral images of scenes containing complex, spatially-varying lighting for use by the colour research community; (iii) providing colorimetrically and perceptually accurate colour for augmented reality applications; (iv) further developing a new theory of how colour discrimination varies with hue; and (v) understanding human vision in terms of compressive sensing. The research budget is chiefly for the training of highly qualified personnel; namely, support of student salaries and their conference travel. My previous students now all have successful careers in the colour-imaging field.

数字成像、人类感知、计算机视觉和 AR/VR/MR 的计算颜色方法 该提案涉及不同“观察者”（不同的人、不同的相机）以及在不同的灯光（日光、LED、荧光灯、钨丝灯）下如何感知物体的颜色。颜色是一个非常跨学科的领域，涉及心理学、哲学、化学、物理学和计算机科学。我理解颜色的方法是将颜色感知视为一个计算过程。因此，我的实验室开发的颜色感知模型被制定为算法，可以通过它们是否简单地提供预期结果来进行测试，其次可以根据它们的运行方式是否与心理学家进行的心理物理实验中已知的人类颜色感知相一致来进行测试。理解和建模颜色感知的根本困难在于，由于人类只有 3 种类型的颜色敏感视锥细胞，因此进入眼睛的光波长与感知颜色之间不存在一一对应的关系。还有许多其他困难，例如相同的反射光谱在不同的背景下可能看起来不同，这些都有助于颜色成为一个令人着迷的研究领域。然而，这些困难给数码相机行业、数字印刷行业、数字显示行业、纺织行业、照明行业、颜色的科学使用（例如在医疗应用中）、艺术品的数字保存以及最近的增强/混合现实应用中的颜色准确性带来了问题。该提案中的研究项目解决了直接应用于所有这些技术领域的色彩科学的基本问题。拟议研究的目标建立在我实验室的最新进展的基础上，包括同色异谱、颜色恒常性及其限制的工作，建立所有理论上可能的颜色集，评估光的显色特性，以及评估数码相机的颜色准确性。拟议的目标包括：（i）一种新的光源不变的对象分类和识别方法，对机器学习具有普遍意义； (ii) 建立一个数据集，其中包含包含复杂、空间变化照明的场景的多光谱图像的准确地面实况，供色彩研究界使用； (iii) 为增强现实应用提供比色和感知上准确的颜色； (iv) 进一步发展关于色彩辨别力如何随色调变化的新理论； (v) 从压缩感知的角度理解人类视觉。研究经费主要用于高素质人才的培养；即支持学生工资和会议旅行。我以前的学生现在都在彩色成像领域取得了成功的职业生涯。