Motion Analysis in Biological and Computer Vision Systems

视觉运动的测量和使用是生物和机器视觉系统的基本组成部分，为导航、物体操纵和识别等任务提供必要的感官信息。在理解视觉系统如何解决检测突然运动、根据运动不连续将科学分割成不同的物体、跟踪感兴趣的物体、恢复物体表面的三维结构和运动等单个问题方面，已经取得了重大进展。并推断它们自己相对于环境的运动。本研究探讨了如何将这些问题的解决方案集成到运动分析中，以速度，准确性，可靠性和灵活性执行这些功能。这样的系统必须包含多种计算策略，结合快速和稳健的方法来获得定性的运动信息和较慢的，准确的方法来获得三维结构和运动的定量模型。本项目采用的方法将理论分析、计算机算法的实现和测试以及对人类运动感知的观察结合在一起。这项研究将大大提高计算机视觉系统在分析动态图像方面的性能，并对人类视觉系统中的运动分析有新的认识。

The measurement and use of visual motion is a fundamental component of biological and machine vision systems that provides essential sensory information for tasks such as navigation, object manipulation and recognition. Significant advances have been made toward understanding how vision systems might solve the individual problems of detecting sudden movements, segmenting the scence into distinct objects on the basic of motion discontinuities, tracking objects of interest, recovering the three-dimensional structure and movement of object surfaces, and inferring their own movement relative to the environment. This research examines how solutions to these problems are integrated into a motion analysis that performs these functions with speed, accuracy, reliability and flexibility. Such a system must embody multiple computational strategies that combine fast and robust methods for deriving qualitative motion information with slower, accurate methods for deriving quantitative models of three- dimensional structure and motion. The approach taken in this project brings together theoretical analyses, implementation and testing of computer algorithms, and observations on human motion perception. This research will lead both to significant improvements in the performance of computer vision systems at analyzing dynamic images, and new understanding of motion analysis in the human visual system.