Master of Science in Computer Vision (MSCV)
Computer vision is the study of acquiring and interpreting visual imagery. With the exponential growth of digital images and videos captured by cameras, the automated understanding of our visual world has never been more important.
The Robotics Institute is home to one of the largest academic groups for computer vision with expertise in a wide variety of relevant sub-areas.
The MSCV degree prepares students for industry work in a career related to computer vision. The 16-month program features a full-time graduate level course load.
Students enrolled in the MSCV program will have access to world-class computer vision facilities and a comprehensive list of courses offered by the faculty. The courses are the focus of the program, complemented by a culminating experience of a hands-on team project.
The MSCV Program strives to do the following:
- Provide a robust set of courses encompassing current and emerging state of the art computer vision topics that will prepare students for careers in this field.
- Facilitate hands-on experience on real projects addressing current applications of computer vision. Students will be assessed via a final project report, coupled with a demonstration and presentation.
The field is advancing rapidly and its applications continue to expand in areas of great societal value. In recent years, computer vision has changed the way we view the world. Applications include image-based Internet searches, street-view related applications, robotics, face recognition for social networks, safety systems on vehicles, visual product identification and searches, human-computer interfaces for visual communication and gaming, disease diagnostics using medical imaging, visual inspection of machine parts, visual crop quality assessment, and more.
To support the rapid development of these applications, major companies including Adobe, Amazon, Apple, Canon, Facebook, GE, Google, IBM, Microsoft, NVIDIA, Qualcomm, Samsung, and Siemens as well as numerous start-ups are forming computer vision groups.
Upon successful completion of the MSCV program students are expected to be proficient in:
- Reading and understanding current research publications about state of the art computer vision techniques.
- Using the fundamental development tools commonly used for developing computer vision applications.
- Implementing computer vision applications based on state of the art algorithms.
- Presenting the background and implementation details of a state of the art computer vision technique in a concise and clear manner.
- Conducting experimental analysis and testing consistent with current practice in computer vision, including standard metrics and benchmark datasets.
- Applying mathematical and machine learning tools, such as geometry, optimization, and statistics to computer vision applications.
For more information, contact ms-cv@ri.cmu.edu.