Human intelligence seems so mysterious that we have not successfully
understood its foundation until now. Here, I want to present a basic cognitive
process, motion mapping cognition (MMC), which should be a nondecomposable
primary function in human vision. Wherein, I point out that, MMC process can be
used to explain most of human visual functions in fundamental, but can not be
effectively modelled by traditional visual processing ways including image
segmentation, object recognition, object tracking etc. Furthermore, I state
that MMC may be looked as an extension of Chen's theory of topological
perception on human vision, and seems to be unsolvable using existing
intelligent algorithm skills. Finally, along with the requirements of MMC
problem, an interesting computational model, quantized topological matching
principle can be derived by developing the idea of optimal transport theory.
Above results may give us huge inspiration to develop more robust and
interpretable machine vision models.

人类智能是一个谜，直到现在我们仍未完全理解其基础。本文介绍了一种基本的认知过程，运动映射认知（MMC），它应该是人类视觉中不可分解的主要功能。在其中，我指出 MMC 过程可以用来解释大部分的人类视觉功能，但无法通过传统的图像处理方式（包括图像分割、物体识别、物体跟踪等）有效地进行建模。此外，我提出 MMC 可能被视为对陈氏拓扑感知理论在人类视觉上的扩展，并且似乎无法通过现有的智能算法技巧来解决。最后，根据 MMC 问题的要求，我们可以通过发展最优输运理论的思想，得出一个有趣的计算模型，即量化拓扑匹配原则。以上结果可能给我们以巨大的启发，以开发出更强大和可解释的机器视觉模型。