Group Travel Grant for the Doctoral Consortium of the IEEE Conference on Computer Vision and Pattern Recognition

该项目支持2013年6月在俄勒冈州波特兰市举行的IEEE计算机视觉和模式识别会议（CVPR）博士联盟。CVPR是计算机视觉领域最重要的年度会议，约有2000名高年级学生和学生参加，在北美举行，由国际研究界的成员参加。博士联盟的目标是突出即将完成学位的高级博士生或应届毕业生的工作，并为这些学生提供机会与与他们专业知识相匹配的高级研究人员讨论他们的研究。美国国家科学基金会将资助入选的美国研究生参加会议的部分费用。这个项目的智力价值在于选择高质量的博士生，他们的研究得到展示，并由高级研究人员向他们提供反馈。在许多情况下，从不同机构的专家那里获得关于他们的研究和职业规划的建议的机会，并且可能有不同的观点，在自己的机构内部是无法获得的。该项目的更广泛影响包括支持计算机视觉领域一些最聪明的初级研究人员的职业发展，通过引起对研究生发展的一个重要方面的关注，为整个研究界做出贡献，并可能增加STEM领域活跃的研究人员和教师的数量。博士联盟活动的目标是在性别、种族背景、学术机构和地理位置方面有来自不同群体的代表。

This project supports the Doctoral Consortium held with the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) in Portland, Oregon, in June 2013. CVPR is the premier annual conference with about 2000 senior and student participants in computer vision, held in North America and attended by members of the international research community. The goal of the Doctoral Consortium is to highlight the work of senior Ph.D. students, who are close to finishing their degrees, or recent graduates, and to give these students the opportunity to discuss their research with senior researchers matched with their expertise. NSF support covers some of the costs for the selected US graduate students to attend the conference. The intellectual merit of this project rests in the selection of top-quality Ph.D. students whose research is showcased and to whom feedback is provided by senior researchers. The opportunity to receive advice on their research and career plans from experts from different institutions, and with potentially different perspectives, in many cases is not available internally within one's own institution. The broader impacts of this project include supporting the career development of some of the brightest junior researchers in computer vision, contributing to the research community in general by drawing attention to an important aspect of graduate student development, and potentially increasing the number of active researchers and teachers in STEM. The doctoral consortium event aims to have representation from a diverse group of participants in terms of gender, ethnic background, academic institution and geographic location.