Histogram of Oriented Gradients (HOG) is a feature descriptor used primarily in computer vision and image processing. It is particularly effective for object detection, as it captures the structure and shape of objects by analyzing the distribution of local gradients. HOG works by dividing an image into small connected regions, computing the gradient orientation and magnitude within those regions, and then compiling these into a histogram. The resulting descriptor is robust to changes in lighting and can effectively represent the shape of objects, making it widely used in applications like pedestrian detection and facial recognition.
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