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Computer Vision (Lecture + Practice)
8.3068
Dozenten
Beschreibung
Prerequisites: Basic Math
Both the rapid growth of image and video data and new applications such as robotics require automated image processing. This course introduces the basic concepts of artificial vision.
Topics: Image acquisition and representation; mathematical background; basic point operations; linear and nonlinear filtering; morphological pattern recognition; color (perceptual aspects and technical representation); gray-, color- and texture-segmentation; image reconstruction and enhancement; object recognition; compression; applications (e.g., image search in databases). A focus is on object recognition, where topics range from simple edge based methods and template matching over traditional approaches like PCA over Boosting, SIFT and SURF to (deep) neural networks.
Weitere Angaben
Ort: 93/E33: Di. 14:00 - 16:00 (14x),
35/E16: Mi. 10:00 - 12:00 (14x),
69/117: Do. 10:00 - 12:00 (14x)
Zeiten: Di. 14:00 - 16:00 (wöchentlich) - Practice, Ort: 93/E33,
Mi. 10:00 - 12:00 (wöchentlich) - Lecture, Ort: 35/E16,
Do. 10:00 - 12:00 (wöchentlich) - Lecture, Ort: 69/117
Erster Termin: Dienstag, 19.10.2021 14:00 - 16:00, Ort: 93/E33
Veranstaltungsart: Vorlesung (Offizielle Lehrveranstaltungen)
Studienbereiche
- Cognitive Science > Bachelor-Programm
- Cognitive Science > Master-Programm
- Schnupper Uni > Cognitive Science
- Cognitive Science