Administrative InfoLecture by Dr. Slobodan Ilic
Exercises by: Mira Slavcheva, Tolga Birdal
Type: Lecture Module IN2210
Programs: Informatics (Bachelor, Master)
Biomedical Computing (Master)
Robotics, Cognition, Intelligence(Master)
ECTS: 7 Credits
Course Language: English
Time, Location & RequirementsLectures: every Monday from 24.10.2016 at 12:15-14:00h in 00.13.009a.
Exercises: every Thursday from 20.10.2016 at 12:00-14:00h in 00.13.009a.
Consultation hours: Office of the responsible tutor (see names next to the exercise). Requirements:
OverviewComputer Vision, as a relatively young research area, has emerged as a key discipline in computer science. This is not only evident by a growing and highly competitive research community with a high impact factor in computer science, but also by the emergence of numerous vision companies turning research ideas into a myriad of commercial applications. Besides well-known studies of 3D geometry and camera models, object tracking and detection in images and videos becomes one of the principal research directions of modern Computer Vision. The main objective of this course is to provide students with a gradual introduction to modern tracking, detection and recognition techniques developed in the last years. The course will provide in-depth knowledge of image features, their detection and description, matching techniques, key-point recognition, basic and advanced tracking algorithms based on image features and image intensities, basics of structure from motion and bundle adjustment, synchronous localization and mapping algorithms as well as object detection using classification approaches. In the end, the students will have a thorough description of the most important tracking and detection techniques. They should be able to understand and implement those solutions and apply them in reasonably complex problems. The concepts described in this course will be accompanied with brief explanations of the necessary mathematical tools. The participants of this course will be given an important basis to follow the vast and growing Computer Vision literature and use the acquired knowledge to solve new practical problems.
Who should attend this course?Bachelor students in their last years and all Master students that are interested in learning about the modern and well-established concepts and algorithms related to tracking, detection and recognition in Computer Vision, or desire to use those techniques in their research.
Prerequisites: Most of the knowledge required should be part of the normal background in Computer Science, undergraduate/graduate Mathematics and Geometry.
AnnouncementsThe grades have been finalized. Please send us an email by the evening of 10.03. if the update you got in the exam inspection has not been applied correctly. We will transfer the grades to TUMonline at the beginning of next week.
The exam inspection is going to be on Wednesday, 8 March, 11:00-12:30 in room 03.13.036. If you cannot make it then, we offer an additional session on Thursday, 2 March, 11:00-12:30 (please come to this session only if you cannot attend the other one). The summary of bonus points achieved this semester is available here. Please email us in case you are missing from the list or you suspect that your points have been miscalculated. If you have questions regarding the course material, you can come by 03.13.036 on Thursday, 16.02., 13:00 - 15:00, or send an email to firstname.lastname@example.org.
The MIDTERM RESULTS are now available. Only matriculation numbers and scores are shown The overall point distribution is shown on this plot. You can have a look at your exam during the midterm exam inspection which is going to take place on Thursday, 19.01.2017, 14:00-15:00 (after the exercise session) in the CAMP seminar room (03.13.10). If you missed the exam inspection, you can come by 03.13.36 on Monday, 23.01.2017, between 11:30 and 12:15. The current list of registered exercise groups is available here (last update: 30.11., 19:00). The final exam is going to take place on 18.02.2017 at 9:00 in Hörsaal 1.
ExercisesExercise FAQ The exercises will be done in MATLAB and students are expected to do them on their own computer/laptop. In case you do not have your own laptop please let us know by sending an e-mail to: email@example.com. You can also find a short MATLAB tutorial here.
RegistrationYou are required to register via TUMOnline (link)!
HomeworkStudents will be given one week to solve the problems. The exact due dates for each homework are announced next to the exercises on this website and will be mentioned during the exercise sessions. Students have to make groups of TWO students and send the names to firstname.lastname@example.org. After that, those who didn't create groups will be associated to groups based on a random selection and will receive a notification about this. If you are looking for a (TDCV) partner tell us and we will assign you one! During the checking of the exercises each group will have at 15 min to be questioned to answer the questions. All members of the group will be questioned about the algorithms and their implementation, so only those who can prove that they understood both theory and practice will get the respective points. Thus, having a working exercise doesn't mean that everyone in the group is going to get full points. Please note that only exercises which work might get the maximal number of points. There will be no "debugging-correcting"-sessions for your solutions during the exercise reviews! If you have questions, ask them beforehand by either mail or in person. All homework should be submitted through e-mail at least one hour before the exercise session with the following format and information.
|Title:||Tracking and Detection in Computer Vision|
|Professor:||Dr. Slobodan Ilic|
|Information:||2 + 4; 7 ECTS|