At the end of the course the student will: - Know the basic concepts of multimedia data representation including compression standards. - Know the protocols and systems for multimedia communication. - Know the basics of computer graphics, including 3D representation, geometric transformations, rendering, interaction paradigms, and Virtual Reality/Augmented Reality/Mixed Reality applications. - Know the basic principles of visual data processing and interpretation through introductory computer vision and machine/deep learning workflows. - Be able to autonomously understand, design and size simple multimedia systems aimed at both media processing and transmission. - Be able to effectively leverage widely available tools to build such systems. - Be able to critically analyze the structure and performance of such systems. - Be able to use computer graphics systems and tools to create, manipulate, animate, and interact with simple, possibly immersive computer-generated content using tools like Blender and Unity. - Be able to interpret the output of simple computer vision models and relate it to multimedia or interactive application scenarios.

Basic knowledge of computer networks and protocols. Basic knowledge of signal theory concepts. Basic computer usage abilities to experiment with tools, in particular command-line based ones. Fundamentals of geometry. Basic familiarity with programming languages like Python and with object-oriented paradigms.

Introduction to multimedia systems Digital media signals fundamentals (sampling, quantization, resolution) Standards and techniques for multimedia data compression (voice, audio, images, video) Multimedia communication systems (streaming, interactive) Analysis of use cases of some major content providers Computer graphics fundamentals (3D representation, transformations, virtual camera, rendering pipeline, interaction). Introduction to Virtual Reality/Augmented Reality/Mixed Reality technologies and applications. Visual computing fundamentals (building blocks, known networks for basic machine/deep learning tasks, data preparation, training, model evaluation).

The course consists of theoretical parts intertwined with practical ones, partly demonstrated by the teacher with exercises developed during lectures, partly delegated to laboratory activities. Laboratory experiences are planned for all the key course components. Laboratories will be held in regular lecture rooms, and the students are expected to work on their own computers. Laboratory activities may involve the use of graphics suites and tools (open source or free-to-use for personal purposes), programming environments, project templates, and guided notebooks.

Materials and handouts provided by the teachers For further investigation: * Fundamentals of Multimedia, Ze-Nian Li, Mark S. Drew, Jangchuan Liu * Multimedia Networking: From Theory to Practice, Jenq-Neng Hwang * Next-Generation Video Coding and Streaming, Benny Bing * Introduction to Computer Graphics, Foley, Van Dan, Feiner, Hughes, Phillips * The Complete Guide to Blender Graphics: Computer Modeling & Animation, Blain * Hands-On Unity Game Development, Borromeo, Gomila Salas * Deep learning with Python, 3rd Edition. Francois Chollet, Matthew Watson. * Alice's Adventures in a Differentiable Wonderland--Volume I, A Tour of the Land. Scardapane, Simone.

Lecture slides; Lab exercises; Video lectures (current year);

Exam: Written test; Computer-based written test in class using POLITO platform;

The final exam is designed to assess the knowledge and understanding of multimedia data representation, compression and communication techniques, and the fundamental concepts of computer graphics, interactive and immersive applications, and computer vision as well as the ability to select and critically discuss the most appropriate methods for specific application scenarios. The exam is written, it lasts approximately 2 hours, with both open-ended and multiple-choice questions. It is not possible to use textbooks, notes, calculators, or other resources. Each question is assigned a maximum number of points written in the text. The exam grade is the sum of the evaluations of each question. The total number of points exceeds 30, making it possible to earn the “laude” by answering all questions correctly, thoroughly, and appropriately. Since the final exam for the Bachelor's Degree in Computer Engineering is combined with a third-year course, an additional question will be asked during the exam for these courses. The courses for the second semester of the third year (Table C) from which Bachelor's Degree in Computer Engineering students may choose are the following: - Introduction to Embedded Systems Electronics - 8 credits - Introduction to Web Applications - 8 credits - Introduction to Data Science and Visualization - 8 credits - Technologies for IoT Ecosystems - 8 credits - Introduction to Multimedia in Computer Graphics – 8 credits - Prototyping Interactive Systems – 8 credits For those who enrolled in the first year before the 2023/24 academic year and do not have one of the previous courses in their career plan, the course will be Computer Networks. For this course, this is implemented as an additional open-ended question, already included in the written exam, about topics related to the course (multimedia and/or computer graphics). To pass the combined exam it is necessary to answer such a question.

In addition to the message sent by the online system, students with disabilities or Specific Learning Disorders (SLD) are invited to directly inform the professor in charge of the course about the special arrangements for the exam that have been agreed with the Special Needs Unit. The professor has to be informed at least one week before the beginning of the examination session in order to provide students with the most suitable arrangements for each specific type of exam.