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We extract feature points between two similar images and match them, followed by overlaying them together based on the matched points in the bottom row.
Thanks to rapid advances of digital camera and various image processing tools, we can easily create new pictures, images, and videos for various purposes. This in turn results in a huge amount of images in the internet and even in personal computers. For example, flickr, an image hosting website, contains more than five billion images and flickr members update more than three thousands image every minute.
These huge image databases pose numerous technical challenges in terms of image processing, searching, storing, etc. In this class we will discuss various scalable techniques for web-scale image/video databases and novel applications that can utilize such data.
In summary, what you will get at the end of the course:
What you will do:
| # of lecture, date |
Topics and slides |
Related material(s) |
| Sep-4 (Th) | Overview on the course and course policy | Q and A for the course (frequently updated) |
| Sep-6 (Th) Sep-11 (T) | Keypoint localization | |
| Sep-13 (Th) | Scale-invariant region detector | |
| Sep-18 (T) | Descriptors | PA1: get to know basic libraries |
| Sep-25 (T.) Sep-27 (Th) | Intro. to object detection | |
| Oct-4 (Th) Oct-9 (T) | Bag-of-Word approach | PA2: basic image retrieval, Image database |
| Oct-11 (Th) Oct-16 (T) Oct-18 (Th) | Recent image retrieval systems | |
| Oct-23 (T) | Mid-term exam | |
| Oct-30 (T) | Seungwoo, Mingyang | |
| Nov-1 (Th) | Soyoung, Suwon | |
| Nov-6 (T) | Kwangheum, Junghyuk | |
| Nov-8 (Th) | Gayeon, Aurelie | |
| Nov-13 (T) | Project feedback | |
| Nov-15 (Th) | Project feedback | |
| Nov-20 (T) | Florent, Gangwook | |
| Nov-22 (Th) | Jongwook, Donghyun | |
| Nov-27 (T) | Jongin, Soonmin | |
| Nov-29 (Th) | No class, because of attending a conf. (SIGGRAPH Asia) | |
| Dec-4 (T) | Kyunghyun | |
| Dec-6 (Th) | Changhoon, Sungheon | |
| Dec-11 (T) Dec-13 (Th) | Final project presentation | |
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For your presentations, please use the this powerpoint template; paper presentation guideline is available.
For your final report, please use the this latex template
Computer vision resources (papers, code, datasets, etc.):
Paper search:
Acknowledgements:
The course materials are based on those of Prof. Fei-Fei Li, Stanford.
Thank you so much!
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