- 2012 Spring Semester Course
- Instructor:
Prof. Byoung-Tak Zhang
- TAs:
Jun Hee Yoo ( jhyoo@bi dot snu dot ac dot kr ), Ho-Sik Seok
- Classroom: 302-107
- Time: Tue & Thu, 3:30 pm - 4:45pm
- Text:
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Video Search and Mining, D. Schonfeld, C. Shan, D. Tao, and L. Wang (Eds.), 2010.
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Video Mining (The International Series in Video Computing), Azriel Rosenfeld, David Doermann and Daniel DeMenthon (Eds.), 2003.
- References:
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Video Content Analysis using Multimodal Information: For Movie Content Extraction, Indexing and Representation, Ying Li and C.C. Jay Kuo, 2010.
- Evaluation:
- Preliminary project poster and report (20%)
- Final project poster and report (20%)
- Paper presentations (30%)
- 1 open-book exam (20%)
- Attendance and discussion (10%)
- Announcement
- (4/17): Prof. Zhang will present Machine Learning instead of paper presentation.
- (4/24): T.A. will present Ch.8 instead of Hyun-Woo Song.
- (5/3): Byoung-Hee Kim will present "Deep Learning Model" instead of Image Search Practice 4.
- (5/9): Upload templates for final reports and final poster. -here-
- (5/29): Exam date is changed to (5/31) Link fixed (Video Summarization PPT files)
- (6/3): Schedule is changed. (6/5, 6/7, 6/12, 6/14) no class. Do your project, poster2, report2.
- (6/28) : Scoring is finished. please check here.
- Objectives
- The amount of multimedia data containing images, sounds, audio, speech, and video is rapidly increasing due to the widespread use of smart phones and digital cameras combined with mobile webs and social networks. Making sense of these multimedia data is fundamentally important not just for applications in education, arts, entertainment, and web services, but also for basic research in cognitive science, robotics, human-computer interaction, and artificial intelligence. This course gives an introduction to data mining and information retrieval with an emphasis on video search and mining. Course attendants will study a variety of video mining systems to learn the basic algorithms and machine learning techniques to analyze video, image, and audio data with hands-on experience with software systems.
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