Personal notes for ETHz Computer Vision HS2022 written in obsidian flavored but also github flavored markdown. You could also find pdf version but they might not be properly adjusted since I output them directly from my obsidian vault. Using obsidian and topaz theme is mostly recommended.
The notes are mainly adapted from the course slides in a more organized way. Some topics that are not explained in details in the slides are extended in the notes. Materials and papers I used to write these notes are included in the repo and you could find the references in the notes.
You could also find the answer to the assignments.
- Laplacian of Gaussian
- Difference of Gaussian
- Regular Grid
- Interesting Point Detector
- Others
- K-means Clustering
- Quantization
- Histogram, TF-IDF
- Specify Object Model
- Generate Hypotheses/Proposals
- Score Hypotheses
- Precision
- Recall
- Resolve Detections
- Non-maximum Suppression
- Context / Reasoning
- Expectation Maximization Algorithm
- KNN
- Random Forests
- Image Integral and Feature Extraction
- AdaBoost Learning
- Cascade Classifier