Workshop on Shape, Contour and Grouping

形状、轮廓和分组研讨会

• 批准号: 9712426
• 负责人: David Forsyth
• 金额: $ 1万
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-07-01 至 1999-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9712426&HistoricalAwards=false
• 关键词: Workshop; Shape; Contour; Grouping

A new application for object recognition, indexing image sets in digital libraries, demands recognition strategies that are (1) effective in cluttered scenes and (2) effective for objects recognised at a class level - for example, people or animals. These needs can be met by recognition algorithms that interpret the world in terms of stylised properties in shape, shading, texture and colour, which are caled 'primitives.' In this approach, objects are represented by a collection of spatial relationships between primitives. The primitives themselves are used as a source of grouping constraints. Recognition proceeds by grouping together features or regions that could represent a primitive, and then assembling groups of primitives that could have come from an object. There is no explicit 3D reasoning, but the grouping processes may contain a great deal of implicit 3D reasoning. This approach to shape and to recognition unites themes studied in active research programs in computer vision, both in the United States and in the European Community. A joint workshop, involving both US and E.C. participants (for whom E.C. funding will be available), will explore representations that use grouping and symmetry as a recognition strategy. Topics will include: shading primitives, image shape constraints that result from volumetric primitives, building grouping-based representations and overall strategies for object recognition. The workshop will be held in Erice, Sicily, in early 1998. The proceedings will be published as a volume in the Springer Lecture Notes in Computer Science series.

一个新的应用程序识别应用程序，在数字库中使用索引图像集，需要（1）在混乱的场景中有效的识别策略，并且（2）对在班级级别上识别的对象有效，例如，人或动物。 可以通过识别算法来满足这些需求，这些算法以形状，阴影，纹理和颜色在形状，阴影，纹理和颜色上解释世界的算法，这些算法是“原始人”。 在这种方法中，对象由原始人之间的空间关系集合表示。 原语本身被用作分组约束的来源。 通过将可以代表原始的特征或区域分组在一起，然后组装可能来自对象的原始群体组来进行识别。 没有明确的3D推理，但是分组过程可能包含大量隐式3D推理。 这种塑造和认可在美国和欧洲社区中计算机视觉的积极研究计划中研究的主题和认可的方法。 涉及美国和E.C.参与者（将为E.C.的资金提供）的联合研讨会将探索使用分组和对称作为认可策略的表示。 主题将包括：阴影原始，图像形状约束，这些限制是由体积原始的，基于分组的表示形式和对象识别的整体策略。 该研讨会将于1998年初在西西里岛的Erice举行。诉讼将在计算机科学系列的Springer讲座笔记中出版。