CS 5262-0

Brief

This course consists of two parts. In the first half, we will review the central concept of the broad area of multimedia and networking systems. By doing so, we make sure that all the students are ready to get into the second part, in which they will each study one of the cutting-edge multimedia networking systems, such as 3D content streaming to head-mounted displays, distributed extended reality games, machine-learning-enabled multimedia applications, and media-aware network elements. The goal is to have each student finish a research project/report at the end of the semester.

Description

Course keywords: Multimedia Content Preparation, Content Delivery, Networked Games, Virtual/Augmented/Mixed Reality, 3D Video, Immersive Systems, Light-Field Video, 360° Video, Volumetric Video Delivery, Multimedia IoT, Mobile Multimedia, Wearable Multimedia, Peer-to-Peer (P2P), Cloud ba<x>sed Multimedia, Multi-Sensory Experiences, Quality-of-Experience (QoE) 1. 課程說明(Course Description) This course covers the latest research in the areas of networking and multimedia systems. Despite the basic concepts of multimedia networking will be reviewed, the course is a graduate-level course and requires each student to work on an intensive term project. Students are expected to regularly present their project progress and build prototype systems based on open-source projects. The expected outcomes include a running testbed along with publishable technical reports. The lectures will be given in English. All the reports must be in English. 2. 指定用書(Text Books) - Li, Drew, and Liu, Fundamentals of Multimedia, 3rd Ed., Springer, 2021 (available online on campus). - Kurose and Rose, Computer Networking: A Top-down Approach, 8th Edition, Person, 2022. 3. 參考書籍(References) - Students will search, print, read, and present the latest search papers under the guidance of the instructor. 4. 教學方式(Teaching Method) Each student will propose and carry out a research project. We will work on well-known multimedia grand challenge problems. Before the end of the semester, each graduate student is expected to generate a research paper, while each undergraduate student is expected to produce a good demo paper. Students who do not deliver publishable reports at the end of the semester will fail the course. 5. 教學進度(Syllabus) The following tentative topics will be presented by the instructor, if not all students are familiar with them already. - Internet Architecture and Services - Audio/Video Coding Overview - Scalable Video Coding - Adaptive Multimedia Streaming - Stream Synchronization - Streaming to Wireless and Mobile Devices - Content-aware Multimedia Streaming and Storage - 3D Mobile Video The following is not an exhausted list of the latest research topic in multimedia networking: - Volumetric videos streamed to head mounted displays (3DoF+ or 6DoF) - Multimedia Internet-of-Things - Media-Aware Network Elements - Virtual Reality and Augmented Reality - 3D Scene Reconstructions - Machine-learning Enabled Multimedia - Point Cloud Compression - Multimodal Speaker Recognition in Video Conferences - Decentralized Social Media 6. 成績考核(Evaluations) - Quizzes: 30% - Grand challenge project: 20% - Term paper: 40% - Open-source contributions: 10% Note that students who do not deliver publishable reports at the end of the semester will receive failing grades. 7. AI 使用規則 (Usage of AI) Conditionally open: Generative AI should not be used during the close-book quizzes. Students can use generative AI to polish their writing, but they should carefully check the outputs of the AI engines instead of blindly submitting them. Students must explicitly acknowledge AI engines in all submitted materials that were processed/influenced by the AI engines. Failing to disclose the involvement of AI engines will lead to a grade penalty. 8. 可連結之網頁位址 https://nmsl.cs.nthu.edu.tw/courses/

Timetable

Scores

Average GPA 3.38

Std. Deviation 1.3

Remarks

16週課程。先修科目CS3570 Introduction to Multimedia and EECS3020 Introduction to Computer Networks

Restrictions

Compulsory

Elective

Cross Discipline

First Specialization

Second Specialization