REU Site: Research Experience for Undergraduates in Computer Vision

这是计算机视觉本科生研究经验（REU）网站的延续，该网站已在中佛罗里达大学运营了36年。每年，10名学生将参加为期10周的全日制暑期课程，沉浸在培养研究生的环境中。参与者将接受培训，开始进行计算机视觉方面的研究；特别是，他们将学习计算机视觉的基础知识，它在许多领域发挥着重要作用，包括安全，医疗保健，国防，商业和制造业。该项目将为来自本科院校的本科生提供机会，让他们与一个非常成功的研究小组一起度过一个夏天。参与者参加短期课程，将自己与他们最想要的项目主题相匹配，并花足够的时间进行重点研究。然后，他们可以选择继续与教授一起写研究论文，准备gre考试和申请研究生课程。我们的REU模式会在其他学校推广。该项目包括开发新的计算机视觉算法，用于解决隐私保护活动和事件识别、大型视觉语言建模、基础计算机视觉模型、图像和视频地理定位、视频对象分割、视频数据浓缩以及相关问题等方面的科学问题。这涉及到理论和实践；我们对困难视觉问题的数学建模和分析以及开发算法感兴趣，同时建立真实的系统，在现实生活中展示这些解决方案。这个项目将加强参与者的以下技能：编写复杂的计算机程序；就研究问题进行口头沟通；想想现实生活中的计算机视觉问题；阅读和理解重点研究论文；参与一个计算机视觉问题的讨论；同时，考虑一下毕业后的职业道路。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This is a continuation of a Research Experience for Undergraduates (REU) site in Computer Vision which has operated at the University of Central Florida for the past thirty-six years. Each year, 10 students will participate in a 10-week duration, full-time Summer program, immersed in a nurturing graduate environment. Participants will be trained to begin to conduct research in Computer Vision; in particular, they will learn fundamentals of computer vision, which plays an important role in many areas, including, security, healthcare, defense, commerce and manufacturing. This project will provide opportunities to a diverse group of undergraduates, most from predominantly undergraduate institutions, to spend a summer with a highly successful research group. Participants take the short course, match themselves to a project topic that they most desire, and spend sufficient time in focused research. They then can opt to continue through the year by working with the professors to write research papers on their project, to prepare for the GREs and to apply to graduate programs. Our model for REU will be disseminated among other schools. This project includes development of new computer vision algorithms for solving scientific problems in privacy preserving activity and event recognition, Large Visual Language modeling, foundation computer vision models, image and video geo-localization, video object segmentation, data condensation in videos, and related problems. This involves both theory and practice; we are interested 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. This project will strengthen the following skills in a participant's ability to: write complex computer programs; communicate orally about research problem; think about computer vision issues in real life problems; read and understand key research papers; contribute to discussion of a computer vision problem; and, consider following a pathway towards a graduate career.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.