👉 Portraits math, often associated with the field of computational photography and image processing, involves using mathematical techniques to enhance, manipulate, or generate images, particularly focusing on portrait photography. This includes algorithms for skin smoothing, background blur (bokeh), color correction, and depth estimation to create realistic or artistic effects. Techniques like convolutional neural networks (CNNs) are employed to analyze and modify images, enabling features such as portrait segmentation, where the subject is isolated from the background, and style transfer, which applies the aesthetic of one image to another. These methods leverage linear algebra, calculus, and machine learning to produce visually appealing and contextually accurate portraits.
