CAREER: The Role of Perceptual Organization in Motion Analysis

二维组织结构的几何和光度属性的演化不仅可以为潜在的结构和运动提供证据，而且可以帮助推断复杂的运动。 这项研究将发展一种计算理论，从长距离的图像中提取结构和运动信息， 图像序列，利用知觉组织原则。 简单的运动将被分组以推断复杂的运动。 将开发一个有效的计算框架来监测组织结构的演变。二维组织的检测是基于图论和投票方法，以及贝叶斯网络的修改。然后通过图像序列跟踪这些2D组织，以生成其光度和几何属性的轨迹。这项研究将开辟新的工具，运动理解使用组织原则的发展的可能性。

The evolution of geometric and photometric attributes of 2D organizational structures can not only provide evidence for the underlying structure and motion but also help infer complex motions. This research will develop a computational theory to extract structural and motion information from long image sequences by exploiting perceptual organizational principles. Simple motions will be grouped to infer about complex motion. An efficient computational framework will be developed to monitor the evolution of the organizational structures. Detection of the 2-D organizations isbased on graph theory and voting methods, and a modification of Bayesian networks. These 2D organizations are then tracked through the image sequence to generate traces of their photometric and geometric properties. This research will open up possibilities for the development of new tools for motion understanding using organizational principles.