REU Site: Research Experience for Undergraduates in Computer Vision

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.