Workshop on Hybrid Neuro-Computer Vision Systems

人类视觉系统代表了最复杂的信息处理机器，具有在不同姿态、照明和尺度下一眼识别物体的独特能力。神经成像和传感设备的最新进展使视觉研究处于激动人心的时刻。 我们现在可以看到大脑在执行复杂的视觉识别和场景理解时“在行动”。 诸如EEG、MEG、fMRI和眼动跟踪等模式已经产生了识别人类视觉处理器所使用的潜在信息处理策略的神经相关性。最近的计算机视觉研究也取得了一些有希望的成功，但主要是针对约束问题。该研讨会汇集了视觉神经科学，神经计算和计算机视觉领域的世界领导者，讨论我们目前对大脑如何能够快速识别物体并分析视觉场景的理解相对于最先进的计算机视觉系统的能力。 重点是识别人类和机器视觉之间的协同作用，以及可用于创建混合视觉系统的潜在神经接口。另一个重点是快速场景分析和识别，而不是推理和更高层次的认知。讲习班的目的是扩大影响，促进三个不同领域的专家之间富有成效的互动。主要成果包括一份报告，详细记录了重大的研究挑战，机遇以及NSF和其他资助机构的具体行动建议。

Human visual systems represent the most complex information processing machines, with unique capabilities in recognizing objects at a glance, under varying poses, illuminations and scales. Recent advances in neuroimaging and sensing device makes this an exciting time in vision research. We can now see the brain "in action" while it performs complex visual recognition and scene understanding. Modalities such as EEG, MEG, fMRI, and eye tracking have yielded identifying neural correlates underlying information processing strategies used by the human visual processor. Recent efforts of computer vision research have also yielded some promising successes, though mostly for constrained problems. This workshop brings together world-leaders in the fields of visual neuroscience, neural computing, and computer vision to discuss our current understanding of how the brain is able to rapidly recognize objects and analyze a visual scene relative to the capabilities of state-of-the-art computer vision systems. Emphasis is placed on identifying synergies between human and machine vision and potential neural interfaces that could be used to create hybrid vision systems. An additional focus is on rapid scene analysis and recognition, rather than reasoning and higher level cognition. The workshop aims at broader impacts in facilitating fruitful interaction among experts from three separate fields. The major outcome includes a report that documents in detail the grand research challenges, opportunities, and concrete recommendations of actions for NSF and other funding agencies.