RI: Small: Enabling robust visual intelligence using propagators to model human competence

研究人员通过询问是什么使人类既聪明又有强大的智慧来解决强健智力的问题。部分答案是，人类具有独特的视觉能力，能够看到、报告他们看到的东西，并利用视觉事件——无论是真实的还是想象的——根据需要回答问题，并形成对物质世界的常识理解。如果要理解和设计强大的人类智能，那么就有必要了解人类的视觉能力。为了理解人类的视觉能力，有必要了解大脑的结构如何使零碎和模糊的感知与期望保持一致，从而产生对视觉世界的理解。为了将对人类视觉的理解提升到一个新的水平，研究人员使用传播者范式对人类视觉系统进行建模，这是一种适合视觉系统所面临的计算问题的思想集合的标签。传播器本身是无状态的，这使得它们适合对视网膜阵列进行操作。此外，传播器连接信息单调增加的单元，确保收敛。最重要的是，双向信息流是传播者范式的核心，因此，当增强了专门针对视觉处理的新功能时，视觉信息不仅从下向上流动，而且从上向下流动，一般来说，从任何模块到任何其他模块，就像信息流在人类大脑中专门用于视觉的许多大脑中心之间流动一样。例如，研究人员注意到，侧膝状突起是信息从视网膜流向初级视觉皮层的中继站，它从初级视觉皮层本身接收大部分输入。研究人员的动机不仅是理解人类视觉的愿望，而且是建立目前远远超出艺术水平的视觉应用的愿望。为了推动他们的工作，他们专注于一个动态场景理解问题：给定一个城市场景和一个或多个固定摄像机，识别诸如走、跑、停、放下、拿起、掉、给、拿、跟着、进入和离开等动作。

The investigators approach the question of robust intelligence by asking what it is that makes humans both intelligent and robustly intelligent. Part of the answer is that humans are uniquely able to see, to report on what they see, and to use visual events--- both real and imagined---to answer questions on demand and to develop a common sense understanding of the physical world. If robust human-level intelligence is to be understood and engineered, then it is necessary to understand human visual competence. To understand human visual competence, it is necessary to understand how the architecture of the brain enables fragmentary and ambiguous perceptions to be brought into alignment with expectations so as to produce an understanding of the visual world.To take understanding of human vision to the next level, the investigators model the human visual system using the propagator paradigm, a label for a collection of ideas suited to the computational problems faced by vision systems. Propagators themselves are stateless, which makes them appropriate for operation on retinotopic arrays. Also, propagators connect cells in which information monotonically increases, assuring convergence. Most importantly, bi-directonal information flow lies at the core of the propagator paradigm, so when augmented with new capabilities tailored specifically to vision processing, visual information flows not only from the bottom up but also from the top down and, in general, from any module to any other module, just as information flows to and from the many brain centers devoted to vision in the human brain. The investigators note, for example, that the lateral geniculate, a relay station for information flowing from the retina to primary visual cortex, receives most of its input from the primary visual cortex itself.The investigators are motivated not only by a desire to understand human vision, but also by a desire to build vision applications now far beyond the state of the art. To drive their work, they concentrate on a dynamic scene understanding problem: given an urban scene and one or more stationary cameras, recognize actions such as walk, run, stop, put down, pick up, drop, give, take, follow, enter, and leave.