COMP 790-096: Computer Vision and the Web
Fall 2007, Tuesdays 3:30-4:30, SN 115
Instructor: Svetlana Lazebnik (lazebnik -at- cs.unc.edu)
Over the last few years, we have seen an explosion in the sheer amount of image and video data available to us over the Internet. The number of images indexed by Google and Yahoo is growing exponentially, and has currently reached several billion. But the revolution is not only technological, it is also cultural, giving rise to the phenomenon popularly referred to as Web 2.0. Part of this phenomenon is the emergence of digital communities like Flickr and YouTube that enable users to upload, tag, and share images and videos with millions of other users.
The wealth of images on the Internet is beginning to revolutionize computer vision. Researchers in object recognition are already taking advantage of the Internet for dataset collection and automatic discovery of object categories. But apart from simply using the Internet as a source of data, computer vision research can play a significant role in helping people to navigate the chaotic sea of visual information. More and more exciting Web-related research ideas are showing up in the latest vision and graphics literature. These ideas include organizing large image collections based on semantics or 3D geometry, using the content of these collections to synthesize new pictures through computational photography techniques such as image completion, or enabling users to interact with photos in novel ways, such as creating 3D-popups from their vacation snapshots. The purpose of the course is to get acquainted with these directions and to speculate about promising avenues for future research and, more generally, the future role of computer vision in the Web 2.0 revolution (and beyond).
This course is set up for variable credit. The basic format (for one unit) will
consist of a weekly paper reading group. Discussions will emphasize the big
picture and conceptual issues, so there are no formal technical prerequisites.
Anyone with an ability to understand (at a high level) papers from recent computer
vision and graphics conferences can benefit from the course. Interested students
can choose to do additional readings, a report, or a project for higher credit.
Reading List**Starred papers are not on the presentation list. But feel free to read them for your own enlightenment or to incorporate them into your presentations if they are closely related to your main topic.
From 2D to 3D
Pictures and words
Learning visual models from Google image search
Learning basic image properties
Indexing and retrieval in large datasets