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Computer Science
Computer Vision
Computer Vision with OpenCV
1. Introduction to OpenCV
2. Core Operations and Data Structures
3. Image Processing Fundamentals
4. Histograms and Image Analysis
5. Feature Detection and Description
6. Object Detection and Recognition
7. Video Analysis and Object Tracking
8. Advanced Image Processing
9. Camera Calibration and 3D Vision
10. Deep Learning Integration
Video Analysis and Object Tracking
Background Subtraction
Background Modeling Concepts
MOG2 Background Subtractor
Gaussian Mixture Models
Learning Rate
Shadow Detection
KNN Background Subtractor
K-Nearest Neighbors Approach
Distance Threshold
Foreground Mask Processing
Optical Flow
Optical Flow Theory
Lucas-Kanade Method
Sparse Optical Flow
Feature Point Tracking
Pyramidal Implementation
Dense Optical Flow
Farneback Algorithm
Flow Field Visualization
Motion Analysis
Object Tracking
Single Object Tracking
MeanShift Tracking
Probability Distribution
Kernel Selection
CamShift Tracking
Adaptive Window Size
Object Scale Changes
Modern Tracking Algorithms
BOOSTING Tracker
MIL Tracker
KCF Tracker
TLD Tracker
MEDIANFLOW Tracker
MOSSE Tracker
CSRT Tracker
Tracker Initialization
Tracker Update Process
Performance Evaluation
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8. Advanced Image Processing