MA-INF 2213 - Computer Vision II

3L + 1E, SS21

Lecturer

Juergen Gall

Content

Tentative: linear methods for classification and regression, boosting, random forests, neural networks, SVMs, prototype methods, nearest neighbors, Gaussian processes, metric learning, structured learning, image classification, object detection, action recognition, pose estimation, face analysis, tracking.

Material

The slides will be provided via sciebo: Slides. The recorded lectures are available at: Videos.

Prerequisites

MA-INF2201 is recommended but not required.

Schedule

The course will be offered as video lecture using zoom. If you have not received access to the video lecture, send an email to Sovan Biswas.

Wednesday, 10:15-11:45

Friday, 10:15-11:45 (every second week)

Start: Friday, 23.04.

Exercises

Theory and programming. At least 50% of the exercise points are required to qualify for exam. The programming exercises are implemented in Python and OpenCV.

Schedule

Friday, 10:15-11:45 (every second week; sometimes on Wednesday)

Exam

Registration period: 01.06.-21.06.

Exam: 9.8.-11.8. (tbc)

2nd Exam: 8.9.-9.9.(tbc)