Integrated Computer Vision System Based on Human Eye Motion

该项目的目标是建立一个机器人视觉系统，模仿人眼运动。特别是，这项研究将导致一个增强的视觉系统，可以实现快速扫描能力（扫视眼球运动）和平滑的对象跟踪能力（平滑追求），以最小的计算开销，并使用廉价的通用硬件。 目前最先进的系统需要大量的计算机后处理和昂贵的硬件。 该项目将产生一种新的摄像机定位系统（硬件）和实时视觉（软件）系统，不需要任何后处理，并实时生成即可使用的图像。为了实现这一目标，该项目借鉴了人类视觉的生物力学和认知原理。创新的方法和算法可以产生速度，准确性和平滑性的运动，以模仿人眼，可以大大提高自动驾驶汽车在农业，军事，安全和交通监控等各种应用中的能力。该项目将为K-12和本科生整合研究和推广活动。该项目研究了一种基于生物动力学的方法，用于协调运动控制和图像处理，其中系统可以通过帧之间的大角度机械地移动视场。这项研究背后的概念是合并系统动力学领域和图像处理领域，而以前的研究只集中在机械设计或图像处理。 该方法的动机是人类视觉的原则，有效的图像去模糊和全景图像拼接。与固有的离散和快速的眼球运动相协调，由眼球生理学启发的所开发的图像处理方法将模仿快速移动的机器人眼睛中的扫视和平滑追踪。 压电驱动的机器人相机定位机制将被用来证明这种眼部生理学启发的方法的有效性。将配置和测试能够同步图像处理和实时运动控制的硬件架构。通过在单个帧速率内去除运动模糊和拼接图像，将从在扫视期间获取的多个图像生成场景的全景图像。系统架构将进行优化，以最佳协调硬件和软件的实时运动控制。

The goal of this project is to build a robotic vision system that mimics human eye motions. In particular, this research will lead to an enhanced vision system that can achieve quick scanning capability (saccadic eye motion) and smooth object following capability (smooth-pursuit) with minimal computational overhead and using an inexpensive generic hardware. Current state-of-the-art systems require significant computer post-processing and expensive hardware. This project will lead to a novel camera positioning system (hardware) and real-time vision (software) system that does not require any post-processing and produces ready-to-use images in real-time. To achieve this goal, the project draws upon the biomechanical and cognitive principles of human vision. The innovative methods and algorithms that can produce motions with speed, accuracy, and smoothness to mimic human eye can greatly enhance capabilities of autonomous vehicles used in a wide variety of applications such as agriculture, military, security, and traffic monitoring. The project will integrate research and outreach activities for K-12 and undergraduate students. This project studies a bio-inspired dynamics-based method for coordinating motion control and image processing where the system can mechanically displace the field of view by a large angle between frames. The concept behind this research is to merge the system dynamics area and image processing area while previous studies focused solely on either mechanical design or image processing. The method is motivated by the principles of human vision for effective image de-blurring and panoramic image stitching. In coordination with inherently discrete and rapid ocular movements, the developed image processing methods inspired by ocular physiology will mimic saccades and smooth-pursuit in a fast-moving robotic eye. A piezoelectrically driven robotic camera positioning mechanism will be employed to demonstrate the effectiveness of this ocular physiology-inspired approach. Hardware architecture that can synchronize image processing and real-time motion control will be configured and tested. A panoramic image of a scene will be generated from multiple images acquired during saccades by removing motion blur and stitching images within a single frame rate. The system architecture will be optimized to best coordinate hardware and software for real-time motion control.