Semester II, 2013-2014 (Wednesdays 6.30 pm - 8.30 pm, SR2 (COM1 #02-04))

Last update: Monday, 19-Jan-2015 17:30:15 +08

Table of Contents

• Announcements (last updated 10-01-2014)
• General Information
• Brief Course Outline
• Course Material
• Assignment Information
• Project Information
• Class Schedule

General Information

Lecturer: Mohan S Kankanhalli

Aims and Objectives:

This course lays the foundation for graduate students to build advanced multimedia computing applications comprising of images, videos, and audio. The module covers the important multimedia computing methods by presenting a comprehensive coverage of the underlying content processing, content transformation and resource optimization techniques in a variety of systems such as multimedia information retrieval, conferencing, surveillance and security. By considering the research issues in the multimedia systems areas, it will also prepare the student in formulating novel approaches for future multimedia computing applications.

Brief Description:

By the end of the course, the students will be familiar with the common computing fundamentals employed in a variety of multimedia applications such as: content-based multimedia retrieval, summarization, surveillance, multimedia security and computational advertisement. The students will be exposed to the core techniques and algorithms spanning across the common and emerging multimedia applications. They will have experience in applying these techniques to novel situations and will be able to do analytical as well as empirical performance evaluation of the particular technique in the overall application context.

Grading information:

Survey Paper: 20%
Assignment: 20%
Project: 60%

Pre-requisites:

• Desirable: CS5240 Theoretical Foundations of Multimedia

Office consultation hours:

• Mohan Kankanhalli   (by appointment)

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Brief Course Outline

* Introduction to Multimedia Computing (2 hrs)
   Motivation; Fundamentals of Multimedia Computing; Image, Video and Audio Compression Overview
* Content-based Retrieval (6 hrs)
   Image Retrieval; Video Retrival; Tagging
* Multimedia Content Processing (4 hrs)
   Multimodal Data Fusion; Visual Saliency & Experiential Sampling
* Multimedia Summarization (2 hrs)
   Video Summarization; Multimedia Simplification
* Multimedia Data Mining (2 hrs)
   Probabilitic Concepts; Image/Video Mining; Concept Mining
* Multimedia Surveillance (4 hrs)
   Background Modeling; Object Tracking; Use of Multiple Sensors; Decision-theoretic Methods
* Multimedia Security (2 hrs)
   Watermarking; Forensics
* Computational Multimedia Advertisement (2 hrs)
   Computational Advertisement Framework; Multimedia Analysis for Ad Placement
* Current Issues & Trends (2 hrs)

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Course Material

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Assignment Information

• Survey Paper is due on Monday, February 10, 2014.
• Assignment is due on Monday, March 10, 2014.

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Project Information

The details of the project will be posted here:

• Project proposal is due on Friday, February 3, 2014.
• The interim project report is due on Friday, March 14, 2014.
• The final project submission is due on Monday, April 14, 2014.

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Class Schedule

15^th Jan (Week 1): Lecture 1: Introduction to Multimedia Computing  

• Reading: Wallace's JPEG Tutorial; MPEG Paper.

22^nd Jan (Week 2): Lecture 2: Content Based Retrieval I  

• Reading: Content-based Image Retrieval at the End of the Early Years; Application Potential of Multimedia Information Retrieval.

29^st Jan (Week 3): Lecture 3: Content Based Retrieval II 

• Reading: Automatic Image Annotation and Retrieval using Cross-Media Relevance Models.

5^th Feb (Week 4): Lecture 4: Content-based Retrieval III 

• Reading: Applications of Video Content-Analysis and Retrieval.

12^th Feb (Week 5): Lecture 5: Multimedia Content Processing I 

• Reading: Information Assimilation Framework for Event Detection in Multimedia Surveillance Systems, Multimodal Fusion for Multimedia Analysis: A Survey.

19^th Feb (Week 6): Lecture 6: Multimedia Content Processing II  

• Reading: Experiential Sampling in Multimedia Systems.

26^th Feb Semester Break

5^th Mar (Week 7): Lecture 7: Multimedia Summarization  

• Reading: Video Summarization using R-Sequences; Compressed Domain Video Summarization; Semantic Video Summarization; Multimedia Simplification.

12^th Mar (Week 8): Lecture 8: Multimedia Data Mining  

• Reading: Multimedia Data Mining: State of the Art and Challenges.

19^th Mar (Week 9): Lecture 9: Multimedia Security  

• Reading: Content-based Watermarking of Images, Compressed Domain Scrambler/Descrambler for Digital Video.

26^th Mar (Week 10): Lecture 10: Multimedia Surveillance I  

• Reading: Adaptive Background Mixture Models for Real-time Tracking. Tracking Paper, Tracking with Kalman Filtering

2^nd Mar (Week 11): Lecture 11: Multimedia Surveillance II  

• Reading: Decision-theoretic Approach to Maximizing Observation of Multiple Targets in Multi-camera Surveillance, Decision-theoretic Coordination and Control for Active Multi-camera Surveillance in Uncertain, Partially Observable Environments.

9^th Apr (Week 12): Lecture 12: Computational Multimedia Advertisement  

• Reading: CAVVA: Computational Affective Video-in-Video Advertising.

16^th Apr (Week 13): Lecture 13: Current Issues & Trends  

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