CAREER: Research and Development of Advanced Visual Information Systems

本研究探讨先进视觉资讯系统（VIS）设计的整合方法。该方法探索了各种重要VIS设计问题之间的最大协同作用-可视化数据索引，压缩，操作和存储。利用图像纹理、颜色、形状等多种特征相结合的集成特征映射来检测和索引图像内容，为基于内容的图像查询提供了有用的方法。探讨了压缩域技术用于提取低层次图像特征。提出了一种改进的四叉树数据结构，用于基于特征的分割和异构特征集成。在前人工作的基础上，直接在压缩域中开发了高效的图像处理算法（如图像滤波和模板匹配），以寻求最小的实现复杂度。研究了实时分层存储系统中多分辨率编码视觉数据的存储策略。所有研究成果将被纳入哥伦比亚大学高级图像实验室的大型集成VIS测试平台。在教育方面，正在开发视觉信号处理和多媒体技术领域的新课程和课程。目前还在研制一种先进的多媒体试验台，以支持研究和教育活动。

This research investigates an integrated approach to the design of advanced visual information systems (VIS). The approach explores the maximum synergy among various important VIS design issues - visual data indexing, compression, manipulation, and storage. An integrated feature map combining multiple image features such as texture, color, and shape is used to detect and index image content, and provide useful methods for content-based image query. Compressed-domain techniques are explored for extracting low-level image features. A modified quad-tree data structure is proposed to be used in feature-based segmentation and heterogeneous feature integration. Based on the prior work, efficient image manipulation algorithms (e.g., image filtering and template matching) are also being developed directly in the compressed domain, in order to seek the minimum implementation complexity. Strategies for storing multi-resolution encoded visual data in real-time hierarchical storage systems are also studied. All research results will be incorporated into an large-scale integrated VIS testbed at the Advanced Imag e Lab of Columbia University. On the educational front, new courses and curriculum in the area of visual signal processing and multimedia technology are being developed. An advanced multimedia testbed is also being developed for supporting research and educational activities.