从计算颜色恒常性视角探究颜色错觉
Investigating Color Illusions from the Perspective of Computational Color Constancy
AI总结：
本研究从计算颜色恒常性视角分析颜色错觉，提出修改现有方法以再现人类感知，并利用错觉参数提升性能，优于专门的多光照算法。
摘要：
颜色恒常性与颜色错觉感知是人类视觉系统中发生的两种现象，它们有助于揭示人类感知的未知机制。数十年来，计算机视觉科学家开发了大量颜色恒常性方法，通过折扣光照来估计表面反射率。然而，颜色错觉在计算颜色恒常性领域尚未被详细分析，我们认为这令人惊讶，因为两者之间的关系意义重大，可能有助于设计更鲁棒的系统。我们主张，任何能够再现我们对颜色错觉感觉的模型，也应能提供光源的逐像素估计。换言之，我们认为对颜色错觉的分析有助于提升现有全局颜色恒常性方法的性能，并使其能够为多光源照明的场景提供逐像素估计。在本研究中，我们分享了调查结果，其中我们采用了几种颜色恒常性方法，并对其进行修改以再现人类视觉系统在颜色错觉上的行为。此外，我们展示了纯粹从错觉中提取的参数能够提升颜色恒常性方法的性能。一个值得注意的结果是，我们基于颜色错觉调查的策略优于那些专门设计用于将全局颜色恒常性算法转化为多光照算法的先进方法。
英文摘要：
Color constancy and color illusion perception are two phenomena occurring in the human visual system, which can help us reveal unknown mechanisms of human perception. For decades computer vision scientists have developed numerous color constancy methods, which estimate the reflectance of the surface by discounting the illuminant. However, color illusions have not been analyzed in detail in the field of computational color constancy, which we find surprising since the relationship they share is significant and may let us design more robust systems. We argue that any model that can reproduce our sensation on color illusions should also be able to provide pixel-wise estimates of the light source. In other words, we suggest that the analysis of color illusions helps us to improve the performance of the existing global color constancy methods, and enable them to provide pixel-wise estimates for scenes illuminated by multiple light sources. In this study, we share the outcomes of our investigation in which we take several color constancy methods and modify them to reproduce the behavior of the human visual system on color illusions. Also, we show that parameters purely extracted from illusions are able to improve the performance of color constancy methods. A noteworthy outcome is that our strategy based on the investigation of color illusions outperforms the state-of-the-art methods that are specifically designed to transform global color constancy algorithms into multi-illuminant algorithms.
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