Multivariate Statistical Analysis and Image Classification with Applications

本研究计画将发展多元统计分析的方法，以应用于统计影像学习、不完全资料、正规化判别分析及相关领域。 研究人员将为多个群体比较，主成分，插补程序，大规模图像分类的聚类和混合建模技术以及统计图像模型的正则化方法开发精确的推断。 该项目的结果将影响图像检索和注释，以及用于分析来自国家小组调查，社会和行为研究，毒理学研究以及多变量不完整数据通常出现的任何领域的数据的统计方法。 由于野生动物研究、环境科学、社会和行为研究、图像分析和相关领域的前沿趋势，需要新的统计和概率思想来分析小样本的统计数据。 研究人员将开发统计公式和计算算法，用于在小样本量下分析此类数据。 主要搜索引擎提供的图像搜索，如谷歌和雅虎，依赖于在包含图像和这些图像的文件名的网页上找到的图像的文本描述。 该项目将促进计算机辅助文字注释图像的技术，从而提高图像在互联网上的可见度。 该项目对社会的其他好处包括外展活动，其中调查人员将参与高中学生的暑期学校课程，以及开发公开的图像分析和判别分析软件。

This research project will develop methodologies in multivariate statistical analysis for the purposes of applications to statistical image learning, incomplete data, regularized discriminant analysis, and related areas. The investigators will develop exact inference for multiple population comparisons, principal components, imputation procedures, clustering and mixture modeling techniques for large-scale image classification, and regularization methods for statistical image models. The results of the project will have impact on image retrieval and annotation, and statistical methods for analyses of data arising from national panel surveys, social and behavioral research, toxicology research, and any area in which multivariate incomplete data commonly appear. Computer software packages for algorithms and analytical tools developed in the project will be documented for public access.Owing to cutting-edge trends in wildlife research, environmental sciences, social and behavioral research, image analysis, and related areas, new statistical and probabilistic ideas are needed to analyze statistical data at small sample sizes. The investigators will develop statistical formulas and computational algorithms for analyzing such data at small sample sizes. Image searches provided by major search engines, such as Google and Yahoo!, rely on textual descriptions of images found on Web pages containing the images and file names of those images. This project will advance the technology of computer-assisted annotation of images by words and hence enhance the visibility of images on the Internet. Other benefits of the project to the society include outreach activities in which the investigators will be involved in summer school programs for high-school students and the development of publicly-available image analysis and discriminant analysis software.