REU Site: NSF Research Experience for Undergraduates in Computer Vision

这个项目代表了计算机视觉本科生网站的研究经验的延续，该网站已在中央佛罗里达大学成功运作了27年。多年来，来自全国65所院校的约270名本科生参加了这一方案。 每年，学生将参加为期12周的全日制暑期课程。 在过去的几年里，很大一部分参与者能够准备一篇论文提交给一个经过评审的会议，论文被接受，然后参加会议提出论文。该计划将建立参与者的这些技能：编写复杂的计算机程序的能力;口头交流研究问题的能力;通过PowerPoint等技术展示自己的项目的能力;做有关项目的海报演示并回答问题的能力;思考真实的生活问题中的计算机视觉问题的能力;对计算机视觉研究论文进行初步阅读的能力;有能力讨论视力问题;有能力申请研究生院。该研究强调开发新的算法来解决视觉地理定位和分割，目标检测，多目标跟踪，活动和事件识别等科学问题。 它推进理论和实践;在数学建模和分析困难的视觉问题和开发算法，而在同一时间建立真实的系统，以证明这些解决方案在真实的生活情况。 该网站采用的教育模式包括由一名教授和一名研究生组成的团队提供全天候的指导;简化的短期课程，让参与者更快地开始他们的研究项目;每天与导师会面，计划全天的活动;在MatLab中进行培训，以快速转变研究思路。参与者参加计算机视觉基础的短期课程，将自己与他们最渴望的项目主题相匹配，并花足够的时间进行重点研究。一些可能的研究项目包括：位置感知语义分割;多目标跟踪与社会行为，模型，人类行为识别等夏天之后，学生可以选择通过与教授合作撰写关于他们项目的技术报告，为GRE做准备并申请研究生课程。

This project represents a continuation of a Research Experience for Undergraduates site in Computer Vision which has operated successfully at the University of Central Florida for the past twenty-seven years. Approximately two hundred and seventy undergraduate students from sixty five institutions all over the country have participated in this program over the years. Each year, students will participate in a 12-week duration full-time Summer program. In past years, a substantial fraction of participants have been able to prepare a paper for submission to a refereed conference, have the paper accepted and then attend the conference to present the paper. The program will build these skills in participants: ability to write complex computer programs; ability to communicate orally about a research problem; ability to present one's project via technology such as PowerPoint; ability to do a poster presentation about the project, and answer questions; ability to think about computer vision issues in real life problems; ability to do initial reading of a research paper in computer vision; ability to contribute to discussion of a vision problem; and ability to embark on applying to graduate school. The research emphasizes development of new algorithms for solving scientific problems in visual geo-localization and segmentation, object detection, multi-target tracking, activity and event recognition. It advances both theory and practice; in mathematical modeling and analysis of difficult vision problems and developing algorithms, while at the same time building real systems for demonstrating those solutions in real life situations. The educational model employed by this site includes round-the-clock mentoring by a team that includes a professor and a graduate student; a streamlined short course that lets participants start their research projects sooner; daily meetings with mentors to plan activities throughout the day; training in MatLab for quick turnaround of research ideas. Participants take the short course on fundamentals of computer vision, match themselves to a project topic that they most desire, and spend sufficient time in focused research. Some possible research projects include: Location-Aware Semantic Segmentation; Multi-target Tracking with Social Behavior, Model, Human Action Recognition etc. After summer, students then can opt for follow-through over the year by working with the professors to write a technical report on their project, to prepare for the GREs and to apply to graduate programs.