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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 fitering; 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 to modern algorithms such as Boosting, SIFT and SURF.

Weitere Angaben

Ort: 93/E42: Mo. 08:00 - 14:00 (10x) Mo. 18:00 - 20:00 (10x) Di. 08:00 - 13:00 (10x), 93/E31: Di. 14:00 - 16:00 (14x) Mi. 10:00 - 12:00 (14x) Do. 10:00 - 12:00 (11x), 93/E06: Do. 10:00 - 12:00 (2x)
Zeiten: Mo. 08:00 - 14:00 (wöchentlich) - Tutorial sessions, Ort: 93/E42, Mo. 18:00 - 20:00 (wöchentlich) - Tutorial sessions, Ort: 93/E42, Di. 08:00 - 13:00 (wöchentlich) - Tutorial sessions, Ort: 93/E42, Di. 14:00 - 16:00 (wöchentlich), Ort: 93/E31, Mi. 10:00 - 12:00 (wöchentlich), Ort: 93/E31, Do. 10:00 - 12:00 (wöchentlich), Ort: 93/E31, 93/E06
Erster Termin: Dienstag, 25.10.2016 14:00 - 16:00, Ort: 93/E31
Veranstaltungsart: Vorlesung (Offizielle Lehrveranstaltungen)

Studienbereiche

  • Cognitive Science > Bachelor-Programm
  • Cognitive Science > Master-Programm
  • Schnupper Uni > Cognitive Science
  • Informatik > Importmodule
  • Cognitive Science