Selected Topics in Video Processing
Study plans 2016-2017 - IMT6161 - 5 ECTS

Prerequisite(s)

  • Fundamental programming and algorithms
  • Fundamental image processing
  • Fundamental video processing

Expected learning outcomes

Expected learning outcomes

Having completed the course, the student should have gained knowledge, skills and general competences related to selected topics in video processing.

Knowledge:

  • The student is in the forefront of knowledge of core issues from different sub-areas of video processing research including video segmentation, video coding, video analyses, multiview video, 3D video, video enhancement and video quality evaluation,
  • He would have achieved in-depth knowledge of one of these core areas through independent study,
  • He would have the ability to discuss (i.e. to describe, analyze, reason about and implement) how digital video may be represented, processed, encoded and transmitted.

Skills:

  • Make appropriate use of mathematical techniques in video processing and analyses. 
  • Demonstrate the use of by implementing techniques such as adaptive algorithms, scalable approaches and real-time techniques to solve problems in video processing applications.

General competences:

  •  Be able to review scientific publications from interdisciplinary areas related to video analyses, 3D and multi-view video, target tracking, activity recognition, and propose new approaches to analyze the video data.
  • The candidate has the ability of appreciation of the impact of (i.e. to describe, analyze, reason about) recently published research in video processing.

Topic(s)

  • Theory and applications of motion estimation
  • Video Coding
  • Video Segmentation
  • Object detection and tracking in video
  • Multi-view video processing
  • 3D video
  • Video Enhancement
  • Video quality evaluation
  • Content-based Video Retrieval

Teaching Methods

Lectures
Net Support Learning
Project work
Meeting(s)/Seminar(s)

Form(s) of Assessment

Other

Form(s) of Assessment (additional text)

Candidates must provide two papers. One is a term paper on a topic chosen by the candidate in coordination with the lecturer (see below), the other is a final report with an other area, beyond that covered by the candidate in the term paper, must be described concisely.

  • Presentation on the selected topic followed by a question and answer session with some practical demonstration of the techniques when possible.
  • A term paper and a final paper.
  • Candidates must pass all parts.

Grading Scale

Pass/Failure

External/internal examiner

Internal examiner.

External examiner (or external and internal) within 5 years period, next time at latest in 2017.

Re-sit examination

The whole course must be repeated.

Coursework Requirements

None

Teaching Materials

Textbooks, monographs, and recent research articles including but not limited to:

  • Gonzalez and Woods: Digital Image Processing, Prentice Hall, 2002.
  • Aghajan and Cavallaro: Multi-camera Networks, Academic Press, 2009.
  • Ristic, Arulampalam and Gordon: Beyond Kalman Filter, Artech House, 2004.
  • MPEG standards reference documents.
  • Recent journal and conference papers.