INTRODUCTION TO MEDIA COMPUTING
2016/2017, Semester 1
School of Computing (Computer Science)
Modular Credits: 4
This module introduces students to (i) the fundamental principles, theory, algorithms, and data structures behind digital representation, compression, synchronization, and processing of image, audio, and video data types, (ii) challenges and issues in developing media-rich applications, such as media streaming and media retrieval; and (iii) design and implementation of multimedia apps. Students will be exposed to the workings of common media file format and common manipulation techniques on media data. After taking the module, students should be confident enough in developing media applications and make appropriate trade-off and design decisions when dealing in media data in their software.
CS1020 or its equivalents.
Schedule for CS2108: Semester 1, 2016/17
Introduction to Media Computing
Liao Lizi / Wang Xiang
Fri 12-1; 1-2 pm (1%)
Mon, 10-12 (VCR: COM1-02-13)
30 Sep (Fri) 12-1 (24%)
23 Nov (Wed), Evening (35%)
3 (14 + 12 + 14) = 40%
L1: Introduction to MM Systems
Outline of Assignments
L2: Brief Intro to Text Retrieval (+RF)
T1: text retrieval models
L3: Image Content Analysis (Feature Extraction & Similarity Measures)
Details Assign1 (image)
L4: Image Retrieval, Indexing & Search
Image Retrieval, Indexing & Search
L5: Basic Concepts in Digital Multimedia
T4: Discussions of Visual & Audio tools
Hari Raya Haji
T5: More Search Examples
L6: Intro to Audio Processing
Submit Assn1 (26/9)
Details Assn2 (Audio)
30/9 (Fri): Mid-Term Test
L7: Image Transformation and Filters
Image filters + Audio
L8: Compression Algorithms [7,8]
Details Assn 3 (Open Project)
T7: compression techniques
L9: Introduction to JPEG [4,9]
T8: JPEG Models
L10: Color Model and Color JPEG
Submit Assn2 (24/10)
T9: Digital Video, MPEG
Grade Assn2 + Assn3 Mtg
L11: MPEG Model [10,11]
: H261 [10,12] &
Submit Assn3 (11/11
T11: H26x &Future Trends
Final Exam (23 Nov, Wed, Evening)
This module introduces students to:
the fundamental principles, theory, algorithms, and data structures behind digital representation, compression, synchronization, and processing of image, audio, and video data types, and
challenges and issues in developing media-rich applications, such as media streaming and media retrieval. Students will be exposed to the workings of common media file format and common manipulation techniques on media data.
See under Schedule
(in groups of 2)
1. Image Search System
due: 26 Sep 2016, Mon 1000
To understand, design and implement a simple fully functional image search system that uses both visual features and text annotation, if any, for the search.
A data set of several hundred images, some with text annotation. Given a query image, the system will return the top 16 search results.
Students should have a good understanding of: (a) the design of a fully functional image search system; (b) the image representation and the various types of visual features and matching algorithms; (c) the combination of text and visual features in the search process; and (d) the extension of system to perform advanced search using latest features. Students also should have good knowledge of the issues and problems of current approaches and their solutions.
2. Audio Search System
(due: 24 Oct 2016, Mon 1000)
To understand, design and implement a simple audio search system.
A data set of several hundred micro-video clips from Vine will be given. Given a query audio clip, the system will search for audio tracks in Vine video to return the top N search results.
Students should have a good understanding of: (a) the design of a simple audio search system; (b) the digital representation of audio and the matching algorithms. Students also should have good knowledge of the issues and problems of current approaches and their solutions.
3. Open Project (Design of a media search app)
(due: 11 Nov 2016, Fri 0900)
To design a technology-oriented media search app on the Web or on mobile device, preferably with proof-of-concept demo. The students should deliberate on the (compelling) use case, novelty and business model of such app.
A complete design of an app that incorporates advanced mm features with a compelling use case. Students should have good appreciation of how practical systems/apps are designed and developed.
3 (14 + 12 + 14) = 40%
Workload Components : A-B-C-D-E
A: no. of lecture hours per week
B: no. of tutorial hours per week
C: no. of lab hours per week
D: no. of hours for projects, assignments, fieldwork etc per week
E: no. of hours for preparatory work by a student per week