研究灵长类的视觉系统机制并以此为基础设计机器视觉的算法已成为重要研究方向,并对机器视觉产生了重要的推动作用。本文从视觉机制和机器视觉方法的角度出发,分析了两大类视觉机制或模型,并列举受其影响和推动的多种重要机器视觉方法:1)合作学习和竞争学习机制,其中合作学习和竞争学习模型相关的机器视觉算法包括立体视觉算法、神经网络、稀疏编码;2)简单细胞和复杂细胞模型,相关的机器视觉算法包括HMAX特征、SIFT描述子和deep belief network。

It has been a promising methodology that designs machine vision algorithms based on the vision mechanism of primate. In this paper, from the intersection points of vision mechanism and machine vision algorithms, we summarize two categories of important vision mechanisms or models, and present their corresponding machine vision algorithms. 1)Cooperative learning and competitive learning: machine vision algorithms motivated by the models typically include stereo vision, neural networks and sparse coding. 2)Simple cell and complex cell: machine vision algorithms corresponding to the models focus on HMAX feature, SFIT feature and deep belief networks.