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CSE 690: Internet Vision
Instructor: Tamara Berg (tlberg -at- cs.sunysb.edu)
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*Announcements*
Dec 10 Reminder project presentations in class on Monday! Here is a basic outline of approximately what you should cover in your presentations, but feel free to add more as time allows. Presentations should be approximately 20 minutes and similar to what you would present if you were giving this talk at a conference. Topics to cover: 1.) Description of the general idea and why it is important. I am available today 10:00am-12:00pm for last minute project questions and also on Friday
1:00-3:00pm. Otherwise I might be available other times on Friday by appointment. Please come
see me if you are having trouble with your project or if you want to run your presentation by
me for input. I also have your grades in the class so far available for pick-up in my office.
Please email me your final presentation, code and images (if applicable) BEFORE class on Monday. If this is too large to email please transfer it to me via a thumb drive.
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Introduction
With the explosion of images and video on the web, dealing with the large amount of unorganized visual data available has become immensely challenging. This course will focus on exploring various types and sources of visual data and how to extract information for effective web search, browsing and other interaction. One of the guiding questions in the course will be: "What can we do with a billion images?". We will explore through reading current papers what new problems and approaches have been proposed by leading researchers in the fields of computer vision, information retrieval, and multi-media. Students will have a chance to define their own problems and work on solutions through a course project. |
Topics
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Tentative Schedule
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Reading List The current reading list is available here. We will choose some subset of these to read based on students' interests. |
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Grading There will be a final project due at the end of term with various checkpoints during the course of the semester. In addition students will be expected to prepare and lead a class discussion summarizing and critiquing a few recent relevant research papers. Lively participation and discussions are encouraged. Since this class focuses on a new and exciting research area there are no required prerequisites although some previous experience with Computer Vision or Machine Learning would be helpful. A brief summary of related algorithms and techniques will be presented at the beginning of the semester. |
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Useful links Matlab Data Computing Features Other Useful Software Reference Books |
Fun Examples of Internet Vision in Action
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