COMPUTER VISION PPT
Instructor:
Instructor:
David Forsyth
slides:
- An Introduction to Computer Vision
- Cameras
- Radiometry
- Sources, Shadows and Shading
- Color
- Linear Filters and Edge Detection
- Pyramids and Texture
- Segmentation by Clustering
- Fitting and Segmentation
- Segmentation and Fitting using Probabilistic Methods
- Tracking using Linear Dynamic Models and the Kalman Filter
- Model-based Vision
- Recognition by Template Matching
- Recognition by Relations between Templates
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