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Prof. Silvio Savarese Office Hour: Wednesday at 4:45 PM, Gates 228 http://cvgl.stanford.edu/silvio/ |
Dr. Kari Pulli (Nvidia) Office Hour: By Appointment https://research.nvidia.com/users/kari-pulli |
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Saumitro Dasgupta Office Hours: Monday 1pm — 3pm, Gates B24A |
Francois Chaubard Office Hours: Thursday 5pm — 7pm, Gates B24B |
The course surveys recent developments in computer vision, graphics and image processing for mobile applications.
Topics of interest include: feature extraction, image enhancement and digital photography, 3D scene understanding and modeling, virtual augmentation, object recognition and categorization, human activity recognition.
As part of this course, students will familiarize with a state-of-the-art mobile hardware and software development platform: an Nvidia Tegra-based Android tablet, with relevant libraries such as OpenCV and FCam. Tablets will be available for each student team.
In the first part of the course students will:
In the second part students will work on a class project as well as present and discuss papers related to state-of-the-art mobile vision applications.
Student will be required to summarize their results into a project write-up and present their projects in class.
Some examples of projects are:
Students will be evaluated on the main tasks above through two problem sets. Each problem set will cover the following areas of computer vision:
Your proposal (maximum 4 pages) should include the following:
Please submit your proposal as a PDF document.
Logistics.
What to cover.
Evaluation.
Class participation.
General Guidelines:
Include the following:
Knowledge of linear algebra, probability, as well as concepts introduced in either CS131 or CS231A and CS232 (or equivalent) are necessary for understanding the material covered in this class. C++ (or Java) programming experience is expected.
3 or 4 — Every student is required to do a course project.
We would recommend posting class related questions on Piazza.
You can also reach the course instructors and TAs at cs231m-spr1314-staff@lists.stanford.edu.