After successful completion of the course, students are able to identify key techniques for visual analysis and vlsualization of human pose and motion by using images and videos, to describes their characteristics, and to judge their applicability to a given application.
The course makes students acquainted with various 2D and 3D techniques for the analysis and visualization of human motion using images and videos. This inludes topics such as motion tracking, human body models, human pose estimation, and the usage of eye-tracking techniques. In particular, the course addresses human action recognition, applications in sports, and selected aspects of human-robot interaction.
The lecture slides will be provided on TUWEL and are supplemented by suitable video material, demos, and weblinks, in order to illustrate the lecture content and current research questions
The preliminary meeting for this course will be held on the 22nd of March 2023 from 10:00 - 12:00 in the Seminarraum FAV 01 B (Seminarraum 187/2) seminar room. The lecture will be held on the following wednesdays from April to June:19.04., 26.04., 03.05., 10.05., 17.05., 24.05. (Possible replacement dates 31.05 und 7.06). Each block will take place in the Seminarraum FAV 01 B (Seminarraum 187/2) seminar room.
The first exam date is planned for the 14.06.2023 from 15:00 - 17:00 Uhr in room FAV Hörsaal 1 - INF. Please take note of the important information on the exam given on the slides in the TUWEL course.
This course and the corresponding exams are planned as in-person sessions. If the circumstances make that impossible, parts of the course will be held in a distance-learning format. If that should be the case, you will be informed in advance!
This course represents 1.5 ECTS (= 38 hours). An estimate of 14 hours of these will be used for the actual lecture and the remaining 24 hours for exam preparation.
Via the written exam, the understanding of the methods and algorithms discussed in the course is assessed by means of textual descriptions, formulas, sketches, pseudocode, etc.
The course requires basic knowledge in image and video processing, as taught in related courses of the Bachelor programme Media Informatics and Visual Computing and the Master programmes Visual Computing and Media and Human-Centered Computing.
