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Computer Vision Laboratory

Est. 1998





About the Lab

The Computer Vision Laboratory (CVL) was established in 1998 to conduct pure and applied research in computer vision. We are a vibrant growing group, contributing to an exciting expanding field. Our goal is to pursue a wide range of applied and theoretical problems across many areas. Members of the lab include faculty, postdocs, as well as graduate and undergraduate students from the Department of Computer Science and Engineering, and various other units from UNR. CVL collaborates extensively with many national labs across the country as well as with industry.

Research projects span a broad range of multidisciplinary topics, such as object recognition, visual motion analysis, 3D reconstruction, face detection/recognition, biometrics (i.e., fingerprint, hand), tracking and pose estimation of human body/head / hand / eye-gaze,surveillance and human activity recognition. Our research is supported by extensive funding from government agencies (i.e., NSF, ONR, NASA) and private industry (i.e., Ford, Motorola).

The laboratory has extensive state-of-the-art facilities for doing research, such as high-performance computers, image capture and display devices, software packages, robotic devices, and many other peripherals. The faculty and students of CVL actively publish their research results in many journals and conferences. Faculty of the lab offer a wide variety of courses in computer vision and related areas such as in pattern recognition and machine learning.

Research Team


Current Faculty

Current Faculty

Previous Faculty

Previous Faculty

Affiliate Faculty

Affiliate Faculty


PhD Students


MSc Students


BSc Students







External Collaborators

External Collaborators

Visiting Scientists



Fall 2019Spring 2019 Older


My teaching is mainly focused on visual computing, interactive gaming, machine learning, and robotics. In the past, I have taught classes in parallel computing, computer architecture, and microprocessors.

CS 328 - Fundamentals of Game Design (Fall 2019)

Game Design Logo Fundamental topics related to game design. Topics include: game design requirements, game design principles, evaluation, peer review, prototyping.
This course requires some basic programming skills and a reasonable background in basic math and linear algebra. Enough background on the required mathematical theories and applications will be provided. Therefore, students should not have major problems understanding the content of the course as long as they follow the book, nd online reading materials.

CS 685/485: Computer Vision (Spring 2019)

Computer Vison Logo Principles, design and implementation of vision systems. Camera models and image formation, feature detection, segmentation. Camera calibration, 3-D reconstruction, stereo vision.
Computer Vision focuses on the development of a theoretic and algorithmic foundation by which useful information about the 3-D world can be automatically extracted and analyzed from a single image or a video sequence of images.
Computer Vision systems have many potential applications. Robots who can understand what they see are more likely to interact with the real world in a satisfactory manner Vision methods can be used to track the trajectory of people and vehicles for traffic monitoring; they can help in the identification of faces for security applications; they can be used for obtaining 3-D models from images, with applications in architecture, medicine, virtual reality, or computer-aided design.

Older Courses

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  • Advanced Level Design
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  • Automata and Formal Languages
  • Parallel Programming
  • Senior Projects in Gaming
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  • AI and Behavioral Modeling
  • Advanced Level Design
  • Gaming Networks Architecture
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  • Game Engines Architecture
  • Multimedia Programming
  • 3D Modeling
  • Advanced Animation
  • Internet Programming
  • Fundamentals of Programmin I, II

News and Announcements

Vision Resources

Sponsors and Grants


Have questions about my research or how to get involved?

We are looking for motivated and intelligent graduate students. If you have any questions about our research or wish to join our team, please contact us.

Computer Science and Engineering Department
1664 North Virginia Street (M.S. 171)
Reno, NV 89557
Laxalt Mineral Engineering Building
LME 314
cvl [at] unr [dot] edu