course-details-portlet

IMT4890 - Specialisation in Video Processing

About

Examination arrangement

Examination arrangement: Oral exam
Grade: Letter grades

Evaluation Weighting Duration Grade deviation Examination aids
Oral exam 100/100 30 minutes E

Course content

In this course we will discuss state of the art video analysis for video understanding and its applications in different domains; e.g. video surveillance and video guided surgery. Actual topics may include but are not limited to the following topics:

  • Video indexing, summarization, and retrieval.
  • Video-based object classification.
  • Audio and video semantic analysis.
  • Object detection and tracking.
  • Video processing in the compressed domain.
  • Multi-camera systems and multi-camera data fusion and processing.
  • Objective video quality evaluation.
  • 3D and multi-view video compression.
  • Deep learning for medical image processing
  • Deep learning for video surveillance

Learning outcome

Having completed the course, the students will - Possess advanced knowledge within the area of intelligent video technology, with emphasis on representing, analyzing, compressing and processing video. - Possess specialized insight and good understanding of the research frontier in selected topics of video analysis especially of relevance to video surveillance, video-based navigation and video guided surgery applications.

Skills and general competence: - Be able to use relevant and suitable methods when carrying out further research and development activities in the area of video analysis and processing - Be able to critically review relevant literature when solving the assigned problem or topic. - Be able to give a presentation and demonstrate their findings.

Learning methods and activities

-E-learning and Seminars:

Additional information: -Lectures by the course instructors and guest lectures by invited experts. Student presentations on selected topics.

E-learning material will be available for this course: PDF of the lectures and student presentations, and possibly audio/video recordings of the lectures will be provided. These E-lectures material will be available on an e-Learning platform (Blackboard). Which will also be used for discussions with the teachers and between the students.

Compulsory requirements: -Oral presentations. Each student needs to study one topic, make a short introductory presentation (5min) about it and later give a deeper presentation (20-30min) and write a report about the work done and its outcomes.

Compulsory assignments

  • Mandatory Project Report

Further on evaluation

Re-sit: One re-sit for the Oral re-examination may be offered for valid reasons only, needs to have given the presentation/implementation and report accepted to be allowed for the re-sit.

Forms of assessment: - 20-30 min Oral Exam, individually (counts 100%, evaluated by lecturers and external reviewer) / video conference via Skype for distance students may be arranged - Topic report (is a pre-requisit to take the exam and is evaluated by lecturers as pass/fail). - Each part must be individually approved of.

Specific conditions

Compulsory activities from previous semester may be approved by the department.

Admission to a programme of study is required:
Applied Computer Science (MACS)
Applied Computer Science (MACS-D)
Colour in Science and Industry (COSI) (MACS-COSI)
Computational Colour and Spectral Imaging (MSCOSI)

Required previous knowledge

Machine learning and image/video processing and analysis or equivalent courses

Course materials

Recent research papers and book chapters from various books. Material will be published on the course pages before the start of the course.

Credit reductions

Course code Reduction From To
IMT5281 5.0 AUTUMN 2017
More on the course

No

Facts

Version: 1
Credits:  7.5 SP
Study level: Second degree level

Coursework

Term no.: 1
Teaching semester:  AUTUMN 2022

Language of instruction: English

Location: Gjøvik

Subject area(s)
  • Computer Science
Contact information
Course coordinator: Lecturer(s):

Department with academic responsibility
Department of Computer Science

Examination

Examination arrangement: Oral exam

Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
Autumn ORD Oral exam 100/100 E 2022-12-01
Room Building Number of candidates
  • * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
Examination

For more information regarding registration for examination and examination procedures, see "Innsida - Exams"

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