Larry S. Davis

Larry S. Davis is a Professor in the Institute for Advanced Computer Studies and the Department of Computer Science. He is affiliated with the Computer Vision Laboratory of the Center for Automation Research, for which he served as the head from 1981-1986. He has been the Chair of the Department of Computer Science since 1999.

NOTE TO PROSPECTIVE GRADUATE STUDENTS: Every Fall I receive numerous emails from prospective graduate students asking about the possibility of doing graduate work at Maryland with me in computer vision. I cannot answer all of these messages, so I am posting a generic reply here:

  1. I work with students in both Computer Science and Electrical and Computer Engineering. Admission into either of these programs is extremely competitive, with more than 1000 applications to each program every year. You must be accepted by one of these programs to join our group.

  2. I generally bring 2-3 new students into the group each year, although typically they are not first year graduate students (whose time is consumed by courses and projects). In computer science, essentially all students accepted into the program are given financial aid.

  3. If you have an exceptionally strong background in computer vision (one or two publications in leading vision conferences or journals), then you might be offered a research assistantship immediately.


  1. Data structures . This page contains the syllabus for CMSC 420, a senior level course on data structures, project descriptions and pointers to pdf files that contain the viewgraphs used for the course.

  2. Computer Vision . This is a senior level introductory course on computer vision. This page contains the course syllabus, presentation materials and project descriptions.

Our sponsors (present and recent past):


Research Scientists

Current Ph. D. Students



Background subtraction

Human detection, face recognition and appearance matching


Camera networks

Human movement modeling

3D Human Motion Capture

Object/Action Recognition/Scene Analysis

Event modeling and recognition

High Performance Computing and Fast Algorithms for Vision