RI: Small: A Generic Mid-Level Representation as Object Part Hypotheses for Scalable Object Category Recognition

本项目开发了一种基于形状和外观的基于碎片的图像中间层表示，其中形状起主要作用。该表示可以以自底向上、独立于类别的方式填充，同时可以由依赖于类别的顶级流程有效地访问。产生物体部分假设的固有模糊性通过标准和新颖的感知操作组合形成替代图像片段来解决，同时考虑到形状和外观，以及基于区域和基于边界的线索。在避免重复的最佳优先图表示下管理碎片数量的指数增长，从而在庞大的碎片池中获得足够数量的诊断可识别对象部件。该项目还探索了通过接近图和几何索引结构将这些片段嵌入到度量相似空间中，以实现有效的最近邻搜索。最终的结果是一个可扩展的、对数对象类别识别的表示空间和索引。这项工作的一个关键方面是，类别本身也在层次相似性空间中表示，这在计算上实现了类似于Rosch？S基本等级分类。这一活动的广泛影响跨越了大量的应用：任何受益于可扩展对象识别的应用，例如数据库索引，例如在商标数据库中搜索，工程图纸和计算机生成的图形，基于内容的网络搜索，空中跟踪和车辆识别，自动动物行为分析等等。

This project develops a fragment-based intermediate-level representation for images based on shape and appearance, with shape playing the primary role. The representation can be populated in a bottom-up, category-independent fashion, which at the same time can be efficiently accessible by top-level, category dependent processes. The inherent ambiguity in generating object part hypotheses is resolved by combinatorially forming alternative image fragments by standard as well as novel perceptual operations, taking into account both shape and appearance, and both region-based and boundary-based cues. The exponential growth of the number of fragments is managed under a best-first graph representation that avoids duplication, leading to a sufficient number of diagnostic recognizable object parts among a vast pool of fragments. The project also explores an embedding of these fragments in a metric similarity space via proximity graphs and a geometric index structures for efficient nearest neighbor search. The final outcome is a representation space and an index for scalable, logarithmic object category recognition. A key aspect of this work is that categories themselves are also represented in a hierarchical similarity space, and this computationally implements ideas akin to Rosch?s basic level categorization. The broader impacts of this activity spans a vast number of applications: any application which benefits from scalable object recognition such as indexing into databases, e.g., searching in a database of trademarks, engineering drawings and computer generated graphics, content-based web search, aerial tracking and recognition of vehicles, automated animal behavior analysis, and many others.