Gaussian Mixture Modeling Method: A Key Approach in Object Detection
The Gaussian Mixture Modeling Method serves as a fundamental technique in object detection systems
AdaBoost (Adaptive Boosting Algorithm)
AdaBoost, or Adaptive Boosting Algorithm, is widely used in object detection, particularly in face recognition applications. This resource originates from a classic textbook, ensuring high reliability and usability. Even if not directly applied, studying the source code provides valuable insights into the algorithm's implementation.
MATLAB Code Implementation of Matched Filter for Ground Penetrating Radar Target Detection
MATLAB matched filter implementation for ground penetrating radar target detection - highly effective with practical code examples and algorithm explanations
Automatic Target Detection Using Background Subtraction with Meanshift Tracking
This program initially employs background subtraction for automatic target detection, then seamlessly switches to meanshift tracking once the target fully enters the image frame.
Endmember Extraction for Hyperspectral Image Target Detection
Endmember extraction method specifically designed for hyperspectral image target detection, demonstrating superior performance with effective algorithmic implementation
Source Code for Target Trajectory Tracking in 2D Images
This program implements target trajectory tracking in 2D images using Kalman filtering. The system employs background subtraction for target detection and feeds the results to a Kalman filter to predict the target's next appearance position (marked in red). The predicted position can be compared with the actual detected position (marked in green).
Target Detection and Recognition in Cloud Background Using Mathematical Morphology
Two distinct methodologies leveraging mathematical morphology for detecting and identifying targets against cloud backgrounds, incorporating algorithmic implementations and practical code considerations.
Space-Time Adaptive Signal Processing
Space-Time Adaptive Signal Processing for SAR Moving Target Detection - ACP and AEP Method Implementation Approaches
Single Gaussian Model Implementation in RGB Color Space
Implementation of a single Gaussian model in RGB color space for object detection, including pixel probability distribution modeling and classification techniques.
MATLAB Code for Face Detection with Viola-Jones Algorithm Implementation
Application Context: Face detection code demonstrating how to detect faces, noses, mouths, and eyes using MATLAB's built-in classes and functions. Based on the Viola-Jones face detection algorithm, the Computer Vision System Toolbox includes the vision.CascadeObjectDetector system for object detection. Prerequisites: Computer Vision System Toolbox must be installed. Key Technology: MATLAB enables face detection through various techniques including boundary setting, edge detection, and utilizing signal processing and image processing tools. This technology serves security purposes by allowing authorized personnel access through comparison with pre-stored facial data.