Data Mining and Information Retrieval
  • 2013 Spring Semester Course
  • Instructor: Prof. Byoung-Tak Zhang
  • TAs: Beom Jin Lee ( bjlee@bi dot snu dot ac dot kr )
  • Classroom: 302-209, 302-311-1
  • Time: Tue & Thu, 2:00 pm - 3:15pm
  • Text:
    1. Video Search and Mining, D. Schonfeld, C. Shan, D. Tao, and L. Wang (Eds.), 2010.
    2. Video Mining (The International Series in Video Computing), Azriel Rosenfeld, David Doermann and Daniel DeMenthon (Eds.), 2003.
  • References:
    1. 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
  • 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.

  • Lecture Schedule
  • Week Topics Presenter Slides
    Week 1 3/5
    • Course Outline
    • Video Search and Mining: Overview
       
    3/7
    • Assignment of Paper Reading
     
    Week 2 3/12
    • MATLAB Practice 1
      ZIP file
    3/14
    • Data Mining & Information Retrieval
    • Machine Learning for Video Mining and Retrieval
     
    Week 3 3/19
    • Efficient Video Browsing (Ch. 1)
    Teklu, 서석준  
    3/21 Temporal Video Boundaries (Ch. 3) 김경민, Margad  
    Week 4 3/26
    • MATLAB Practice 2
      PPT FILE
    3/28
    • MATLAB Practice 3
    WORD file
    Week 5 4/2
    • Video Summarization (Ch. 4)
    황정인,박윤종 dropped
    4/4
    • Mining TV Broadcasts 24/7 for Recurring Video Sequences
    정동석 pdf file
    Week 6 4/9
    • Movie Content Analysis, Indexing and Skimming (Ch. 5)
    김덕주  
    4/11
    • Face Recognition and Retrieval in Video
    오준혁 pdf file
    Week 7 4/16
    • erased
    erased  
    4/18 Image Search Practice 1 ZIP file
    Week 8 4/23
    • Understanding the Semantics of Media (Ch. 8)
    Camilo Celis  
    4/25 Image Search Practice 2 PPT file
    Week 9 4/30
    • Project Poster Presentation 1
       
    5/2 A Human-Centered Computing Framework to Enable Personalized News Video Recommendation (new) 오준혁,Camilo pdf file
    Week 10 5/7
    • Statistical Techniques for Video Analysis and Searching (Ch. 9)
    Anton, Margad  
    5/9
    • Deadline for Project Report 1 (5/9)
    Week 11 5/14
    • Unsupervised Mining of Statistical Temporal Structures in Video (Ch. 10)
    강현수(alone)  
    5/16 Buda's Birthday
    Week 12 5/21
    • Pseudo-Relevance Feedback for Multimedia Retrieval (Ch. 11)
    서석준(alone)  
    5/23
    • Video Repeat Recognition and Mining by Visual Features
    강현수(alone) pdf file
    Week 13 5/28   HERE!!!!
    5/30
    • Exam
    Week 14 6/4
    • Semantic Video Content Analysis
    김경민(alone) pdf file
    6/6 Memorial day  
    Week 15 6/11
    • Visual Concept Learning from Weakly Labeled Web Videos
    Anton,Teklu pdf file
    6/13
    • Poster Presentation 2
    • Deadline for Project Report 2 (6/11)
         
This page is maintained by Beom Jin Lee
Last update: 2013.1.19.