Statistical Shape Models to Aid in Plant Species Identification

帮助植物物种识别的统计形状模型

• 批准号: 0836823
• 负责人: David Jacobs
• 金额: $ 1万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-01 至 2009-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0836823&HistoricalAwards=false
• 关键词: Statistical; Shape; Models; Aid; Plant

Shape analysis is a fundamental problem in computer vision. Object recognition requires comparison of two shapes and determination of similarity. The challenge is that an object?s shape may vary due to articulations, non-rigid deformations, or natural variations between different instances of objects from the same class. It is important to understand how to represent shape, how to match shape allowing for deformation, and how to learn the types of variations that can occur for a particular class of objec5ts. The PI has a number of new approaches to shape matching and has been applying them to the construction of devices for plant species identification. The system can be used to monitor distribution or discover new species. Shape analysis has a wide range of additional applications, from military ones to medical ones. The PI will use the funds to develop new collaborations in statistical models of shape.

形状分析是计算机视觉中的一个基本问题。 物体识别需要比较两个形状并确定相似性。 挑战在于这是一个物体吗？的形状可能会由于关节、非刚性变形或来自同一类的对象的不同实例之间的自然变化而变化。 重要的是要了解如何表示形状、如何匹配允许变形的形状以及如何了解特定类别对象可能发生的变化类型。 PI有许多新的方法来进行形状匹配，并已将其应用于植物物种识别设备的构建。 该系统可用于监测分布或发现新物种。 形状分析具有广泛的附加应用，从军事应用到医疗应用。 PI将利用这些资金在形状统计模型方面开展新的合作。