Non-Parametric Representations of Motions and Actions in Video

PI建议建立一个为期3年的项目，以开发视频序列中未知对象的行为和动作的非参数表示。 该方法是使用模式论的生成式统计建模工具来优化非线性降维工具，以应用于自然图像序列。 应用包括医学或航空图像数据集的配准和去噪，对非刚性和可变形运动的理解，以及基于内容的视频索引。智力价值包括正式的工具，以表明在什么样的真实的世界条件下，技术，如Isomap失败。 合作者的重点是心血管MRI数据的研究，诊断人体运动分析，以及头部损伤的力学促进这些方法在真实的和不同的应用明确的测试。 该提案的更广泛影响包括通过允许MRI成像研究的新实验协议来扩大医疗保健的可及性，并提供支持非结构化环境中人体运动分析的工具。 从视频中提取一般表示支持基于内容的索引，这是国家数字图书馆倡议的多媒体组件的核心。 一个基于网络的门户网站（Wumap）将作为自动生成基于网络的自然模式可视化的国家资源，并将为年轻的K-12学生设计部分。

The PI proposes to establish a 3 year program to develop non-parametric representations of the behaviors and actions of unknown objects in video sequences. The approach is to use the generative statistical modeling tools of Pattern Theory to optimize non-linear dimensionality reduction tools to be applied to natural image sequences. Applications include registration and de-noising of medical or aerial image data sets, understanding of non-rigid and deformable motion, and content based video indexing. The intellectual merit includes formal tools to indicate under what real world conditions techniques such as Isomap fail. Collaborators whose focus is the study of cardiovascular MRI data, diagnostic human motion analysis, and the mechanics of head injuries facilitate explicit testing of these approaches in real and diverse applications. The broader impacts of this proposal include expanding access to healthcare by allowing new experimental protocols for MRI imaging studies, and gives tools that support human motion analysis in unstructured settings. Extracting general representations from video supports content based indexing which lies at the heart of the multi-media component of the national digital library initiative. A web-based portal (Wumap) will serve as a national resource for automatically generating web-based visualizations of natural patterns and will have portions designed for young K-12 students.