REU Site: Research Experience for Undergraduates in Computer Vision

这是一个研究经验的本科生（REU）在计算机视觉网站已在中央佛罗里达大学在过去的36年的延续。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研究;特别是，他们将学习计算机视觉的基础知识，这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。这个项目将提供机会，以本科生的多元化群体，大多数来自主要的本科院校，花一个夏天与一个非常成功的研究小组。 参与者参加短期课程，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。然后，他们可以选择继续通过一年的工作与教授写研究论文对他们的项目，准备GRE和申请研究生课程。 我们的REU模式将在其他学校中传播。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，视频中的数据压缩等相关问题。这涉及理论和实践;我们感兴趣的是数学建模和困难的视觉问题的分析和开发算法，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。该项目将加强参与者的以下能力：编写复杂的计算机程序;口头交流研究问题;思考真实的生活问题中的计算机视觉问题;阅读和理解关键研究论文;参与计算机视觉问题的讨论;并且，在本发明中，该奖项反映了NSF的法定使命，并已被认为是值得通过评估使用的支持基金会的学术价值和更广泛的影响审查标准。

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.