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Computer Science
Computer Vision
Computer Vision and Image Analysis
1. Foundations of Computer Vision
2. Image Formation and Representation
3. Fundamental Image Processing
4. Feature Detection and Description
5. Image Segmentation
6. Classical Object Recognition
7. Deep Learning for Computer Vision
8. Motion and Video Analysis
9. 3D Computer Vision
10. Computer Vision Applications
Image Formation and Representation
Physics of Light and Imaging
Electromagnetic Spectrum
Visible Light Range
Infrared Radiation
Ultraviolet Radiation
Light Interaction with Matter
Reflection Properties
Absorption and Transmission
Scattering Effects
Color Theory
Additive Color Systems
Subtractive Color Systems
Color Constancy
Metamerism
Digital Image Fundamentals
Image Formation Process
Light to Digital Conversion
Sensor Technologies
Pixel Representation
Discrete Sampling
Pixel Neighborhoods
Image Coordinate Systems
Image Resolution
Spatial Resolution
Intensity Resolution
Temporal Resolution
Sampling and Quantization
Nyquist Sampling Theorem
Aliasing Effects
Anti-aliasing Techniques
Bit Depth Considerations
Color Spaces and Models
RGB Color Space
Primary Colors
Additive Mixing
Device Dependencies
HSV Color Space
Hue Component
Saturation Component
Value Component
Perceptual Advantages
Grayscale Representation
Luminance Calculation
Weighted Averaging
Advanced Color Spaces
CMYK for Printing
Lab Color Space
YCbCr for Video
HSL Variations
Camera Models and Geometry
Pinhole Camera Model
Geometric Principles
Camera Matrix Formation
Projection Equations
Lens Systems
Thin Lens Model
Focal Length Effects
Depth of Field
Camera Distortions
Radial Distortion
Tangential Distortion
Correction Methods
Camera Calibration
Intrinsic Parameter Estimation
Extrinsic Parameter Estimation
Calibration Patterns
Calibration Algorithms
Geometric Projections
Perspective Projection
Orthographic Projection
Homogeneous Coordinates
Transformation Matrices
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1. Foundations of Computer Vision
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3. Fundamental Image Processing