ACT/SGER: Object Identification and Classification in Aerial Images

该项目支持数学算法和实现的研究，以表示、操作和分析数据，特别是包括特征检测，以及自然图像的注册和表征。通过建立一类被称为图像蛇的活动轮廓模型，研究人员将开发出一种快速的目标识别方法，用于大量的航空照片。结合求解分段线性信号的高阶非线性pde方法，并结合形状和尺寸约束，最终系统在锁定预定义形状方面应该特别有效。这项跨学科的工作借鉴了流体动力学的数学思想，并结合了来自情报界的数据集。该奖项由美国国家科学基金会和情报界共同支持。数学和物理科学理事会的反恐方法计划支持基础研究和劳动力发展方面的新概念，这些概念有可能为国家安全做出贡献。

AST-0442037BertozziThis project supports research in mathematical algorithms and implementations to represent, manipulate, and analyze data, specifically including feature detection, and registration and characterization of natural images. By building on a class of active contour models known as image snakes, the investigators will develop a fast method for object identification, to be used on large volumes of aerial photographs. Combined with higher order nonlinear PDE-based methods for resolving piecewise linear signals, and with shape and size constraints, the final system should be particularly efficient at locking onto predefined shapes. This interdisciplinary work draws on mathematical ideas from fluid dynamics and incorporates datasets from the intelligence community.This award is supported jointly by the NSF and the Intelligence Community. The Approaches to Combat Terrorism Program in the Directorate for Mathematical and Physical Sciences supports new concepts in basic research and workforce development with the potential to contribute to national security.