lecture: room 42/110, Wednesday 10:00-11:30
tutorials: room 48/379, Wednesday 8:15-9:45
This lecture gives an introduction to models and algorithms underlying modern multimedia search technology.
The focus will be on retrieving image and video content (though other media like text and audio will be touched as well).
Lecture schedule:
block | lecturer | content | details | slides | exercise sheets & materials |
---|---|---|---|---|---|
1 | Adrian Ulges | introduction | course formalities, definitions, history, lecture outline, introduction | slides | sheet |
2 | “ | pattern recognition (supervised) | basic decision theory, classification, classifier combination | slides | sheet material NumPy Website NumPy Tutorial |
3 | ” | pattern recognition (unsupervised) | clustering, dimensionality reduction | slides | sheet material |
4 | “ | text retrieval | document retrieval, retrieval models, relevance feedback, data structures | slides | |
5 | ” | image representation I | definitions, color spaces, features and their properties, invariance | slides | sheet material |
6 | “ | image representation II | local features: interest point detection, patch description, matching | slides | |
7 | ” | similarity search I | applications, prototypical architecture, distance measures, object search | slides | live exercise: pattern recognition user study |
8 | “ | similarity search II | scalability: kd-trees, locality-sensitive hashing | slides | |
9 | ” | visual recognition I | applications, challenges, face detection, face recognition, object recognition, visual words | slides | sheet material |
10 | “ | visual recognition II | object category recognition- SVMs, spatial constellation, research | slides slides | |
11 | ” | visual recognition III | concept detection and concept-based video retrieval, concept selection, research | slides | sheet material |
12 | “ | video representation | shot boundary detection, keyframe extraction, motion estimation, motion segmentation | slides | |
13 | Stephan Baumann | music information retrieval | audio features and meta features, categorization, recommendation (content-based vs collaborative), web mining, … | slides |