The Role Learning in Perceptual Organization of Complex Images

南佛罗里达大学苏迪德分校IIS-9907141萨卡，73,407-12美元。学习在复杂图像感知组织中的作用这是一个为期三年的连续奖项的第一年资助。知觉组织是指有效地将低级基元(如像素、边缘段或区域)分组，以便在最少的领域知识的情况下形成对象假设的能力。这一过程是噪声较低的分割过程和复杂的、计算代价高昂的目标识别过程之间的重要联系。这项工作将解决与计算机视觉中的知觉组织相关的三个主要科学问题：(I)如何通过组装小组特征(组)来有效地形成大组扩展的低级原语？图形光谱的概念是实现这一目的的理想机制。(Ii)如何编码分组参数对图像统计的依赖关系？编码为贝叶斯网络的联合概率分布提供了有效的抽象。(3)学习型潜意识组织的作用是什么？探索的学习的具体作用将有三个方面：(A)学习图像到分组参数映射，(B)从对象模型学习组的形式和相关的层次，以及(C)学习适合于域的基元类型，例如角、纹理区域或边缘。

Abstract IIS-9907141Sarkar, SudeepUniversity of South Florida$73,407 - 12 mos.The Role of Learning in Perceptual Organization of Complex ImagesThis is the first year funding of a three year continuing award. Perceptual organization is the ability to efficiently group low-levelprimitives, such as pixels or edge segments or regions, so as to formobject hypotheses with minimal domain knowledge. This process is anessential link between the noisy low-level segmentation processes andthe sophisticated, computationally expensive, object recognitionprocesses. This work will address three major scientific issuesrelated to perceptual organization in computer vision: (i) How toefficiently form large groups of extended low-level primitives byassembling small groups of features (grouplets)? The concept of graphspectra is an ideal mechanism for this purpose. (ii) How to encodethe dependency of grouping parameters on image statistics? Jointprobability distributions encoded as Bayesian networks offer anefficient abstraction. (iii) What is the role of learning inperceptual organization? The specific roles of learning explored wouldbe threefold: (a) learning the image to grouping parameter mapping,(b) learning the forms of the groups, and the associated hierarchy,from object models, and (c) learning the primitive type, such ascorners, textured-regions, or edges, that is appropriate for a domain.