MIXED REALITY AND WEARABLE VISION

Academic Year 2024/2025 - Teacher: GIOVANNI MARIA FARINELLA

Expected Learning Outcomes

The course aims to provide both theoretical foundations and practical skills for designing and developing mixed reality and computer vision applications for wearable devices, which can be applied in various domains. After introducing the basic concepts of mixed reality and computer vision (egocentric vision), the course will review wearable devices and software tools that are useful for developing intelligent systems capable of assisting humans in different environments where they live and work. The course includes both lectures and practical labs where students will use wearable devices and tools to develop projects that will be part of the final exam.

General learning objectives of the course in terms of expected learning outcomes:

  1. Knowledge and understanding:
    Students will acquire the knowledge and concepts underpinning algorithms for mixed reality and wearable computer vision, particularly the methodologies for creating intelligent systems to support humans.
  2. Applying knowledge and understanding:
    Students will gain practical skills for designing and developing mixed reality and wearable computer vision applications through laboratory activities.
  3. Making judgements:
    Through “homework” assignments proposed by the instructor and in-class discussions, students will develop the ability to independently devise solutions to basic problems they may encounter in the workplace.
  4. Communication skills:
    Students will acquire the necessary communication skills and expressive accuracy in using technical language in the field of mixed reality and wearable computer vision.
  5. Learning skills:
    The course aims to provide theoretical and practical knowledge regarding mixed reality and wearable computer vision. Students will learn algorithms, tools, and devices useful for developing mixed reality and wearable computer vision applications. Software libraries and wearable devices will be used to put into practice the theoretical concepts presented during the course. Specifically, the course aims to train students to:
    a) Understand key concepts behind mixed reality and wearable computer vision
    b) Know a wide range of algorithms, devices, and tools for developing mixed reality and wearable computer vision applications
    c) Understand how to design and develop new applications

Course Structure

Classes are held in the lecture hall with the aid of slides made available to students. Theoretical lectures are interspersed with practical exercises carried out in the same classroom. Students are encouraged to form small working groups to complete the proposed exercises and work on the final project.

Course Material: on the TEAM channel of the course

Required Prerequisites

No specific prerequisites are required. Basic knowledge of development on Unity is useful.

Attendance of Lessons

Attendance is not mandatory but is strongly recommended, particularly for the practical sessions.

Detailed Course Content

  • Introduction to Mixed Reality and Wearable Vision
  • History and Evolution of Wearable Devices
  • Sensors in Wearable Devices
  • 3D Coordinate Systems
  • Models and 3D Modeling for Wearable Vision
  • Algorithms for Wearable Vision
  • SLAM and Object Anchoring
  • Marker-based AR and Plane Recognition
  • Algorithms for Human-Centered Input Handling
  • Rendering Pipeline for Wearable Devices
  • Egocentric Perception and Applications
  • Practical Sessions and Laboratory

Textbook Information

Material provided by the teacher

Course Planning

 SubjectsText References
1Introduction to Mixed Reality and Wearable Vision
2History and Evolution of Wearable Devices
3Sensors in Wearable Devices
43D Coordinate Systems
5Models and 3D Modeling for Wearable Vision
6Algorithms for Wearable Vision
7SLAM and Object Anchoring
8Marker-based AR and Plane Recognition
9Algorithms for Human-Centered Input Handling
10Rendering Pipeline for Wearable Devices
11Egocentric Perception and Applications
12Practical Sessions and Laboratory

Learning Assessment

Learning Assessment Procedures

The exam consists of a project (with a corresponding report) agreed upon with the professor, followed by an oral discussion. The final score will take into account the complexity of the developed project, the report, and the oral presentation. The score is expressed on a scale of thirty, according to the following scheme:

  • 29-30 cum laude:
    The student demonstrates an in-depth knowledge of key concepts and development techniques in mixed reality. They can independently analyze design and implementation problems, autonomously selecting the most appropriate algorithms and technological solutions for developing MR applications. The student applies their knowledge critically and demonstrates excellent communication skills and mastery of technical language.
  • 26-28:
    The student has a good understanding of fundamental concepts and main development techniques in mixed reality. They can correctly identify and apply appropriate algorithms and techniques to solve MR development problems. Communication skills and the use of technical language are good.
  • 22-25:
    The student demonstrates a fair knowledge of the basic concepts of mixed reality. They can address development problems, although not always in-depth, identifying acceptable technical solutions. Communication skills and the use of technical language are sufficient.
  • 18-21:
    The student has a minimum understanding of the fundamental concepts and techniques of mixed reality. Their ability to analyze problems and propose technical solutions is limited, but they can still identify basic solutions. Communication skills and the use of technical language are sufficient but not always appropriate.
  • Exam failed: 
    The student has not reached the minimum required knowledge of the fundamental concepts of mixed reality. They are unable to correctly apply development techniques and show significant shortcomings in the use of technical language.

Examples of frequently asked questions and / or exercises

  • Define “Object Anchoring” and explain how it was used in the project.
  • Describe the functioning of gesture recognition algorithms for human-centered input handling and provide an example of their application.
  • Explain how 3D models are used in wearable vision and describe how they are constructed and integrated into AR applications.
  • Explain the principles of plane recognition and how it is used to place virtual objects in AR environments.
  • Discuss the evolution of wearable devices and how they have influenced the development of augmented reality.