Face Detection Implementation
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Face detection can be implemented using MATLAB programming. One effective approach utilizes the Boosted Cascade of Simple Features algorithm for rapid object detection. This method efficiently detects human faces while maintaining high processing speed. In MATLAB implementation, this typically involves using the vision.CascadeObjectDetector system object, which employs Haar-like features and AdaBoost classifiers organized in a cascade structure. The algorithm works by progressively filtering out non-face regions through multiple classifier stages, where each stage focuses on increasingly complex facial features. By implementing this method, we can accurately detect faces and perform subsequent processing and analysis. Key MATLAB functions include detectObjects() for locating faces in images and insertObjectAnnotation() for visualizing detection results.
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