Statistical Shape Models to Aid in Plant Species Identification

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，如何匹配形状允许变形，以及如何学习类型的变化，可能发生的一个特定类别的对象。 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。

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.