REU/ CAREER: Deformable Shape Models for Image Understanding

REU/ CAREER：用于图像理解的可变形形状模型

• 批准号: 9624168
• 负责人: Stan Sclaroff
• 金额: $ 21.45万
• 依托单位: Trustees of Boston University
• 依托单位国家: 美国
• 项目类别: Continuing grant
• 财政年份: 1996
• 资助国家: 美国
• 起止时间: 1996-07-01 至 2001-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9624168&HistoricalAwards=false
• 关键词: REU; CAREER; Deformable; Shape; Models

The research plan is to develop shape representations for image and video ulderstanding. The approach is to encode shape and motion in terms of nonrigid deformations from prototypical or extremal views. This research builds on previous work in modal matching, an orthogonal shape decomposition for matching, describing, and comparing shapes despite sensor variations and nonrigid deformations. Shape and motion coefficients are expressed in terms of the eigenmodes of deformable shape models. The project extends this modal matching framework in four main directions; comparison metrics, prototype-based shape representations, including intensity information, and encoding motion and shape. Primary system evaluation is on synthetic data sets specifically designed to characterize algorithm limits with respect to noise and deformation. System performance is to be evaluated using a large database of images collected by a world wide web crawler. Towards this end, a web robot is being built. The educational plan addresses course development and teaching in multimedia computing, active engagement of undergraduates in research, and outreach for recruiting a greater number of students from traditionally underrepresented groups in computer science.

该研究计划是开发用于图像和视频理解的形状表示。 该方法是根据原型或极值视图的非刚性变形对形状和运动进行编码。 这项研究建立在模态匹配方面的先前工作的基础上，模态匹配是一种正交形状分解，用于在传感器变化和非刚性变形的情况下匹配、描述和比较形状。 形状和运动系数用可变形形状模型的本征模态来表示。 该项目在四个主要方向上扩展了该模式匹配框架； 比较指标、基于原型的形状表示（包括强度信息）以及编码运动和形状。 主要系统评估是在专门设计用于表征算法在噪声和变形方面的限制的合成数据集上进行的。 系统性能将使用万维网爬虫收集的大型图像数据库进行评估。 为此，正在构建一个网络机器人。 该教育计划涉及多媒体计算方面的课程开发和教学、本科生积极参与研究以及从计算机科学传统上代表性不足的群体中招募更多学生的外展活动。