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face detection algorithm
A face detection algorithm is a computational procedure designed to identify and locate human faces within digital images or video streams. Rather than determining individual identity, which is the function of facial recognition, a face detection algorithm determines whether human faces are present and returns their spatial locations, typically as bounding box coordinates. Early implementations relied on handcrafted feature extractors paired with statistical classifiers, such as the Viola-Jones framework combining Haar-like features and adaptive boosting, whereas modern systems widely employ deep neural networks, particularly convolutional architectures, to handle variations in lighting, pose, and occlusion. These algorithms serve as a foundational component in computer vision pipelines, enabling applications such as camera autofocus, biometric preprocessing, visual surveillance, and augmented reality.
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