Human-face-based real-time depth of field method

Abstract

The invention discloses a human-face-based real-time depth of field method. The method comprises the steps that real-time images are obtained by obtaining real-time viewing camera data, human face detection is carried out on the real-time images to obtain human face areas and human face key points, then, affine transformation is adopted for obtaining transformed human face contour images according to preset human face contour images, preset human face key points corresponding to the human face contour images, and the obtained human face areas and human face key points, finally, the transformed human face contour images are used as the masking of the human face areas of the real-time images for conducting transparency calculation on the real-time images and blurred images to obtain human face depth of field images, and the human face depth of field images are used as display images to be previewed on a screen in real time. No hardware cost is needed, and no manual intervention operation is needed, so that the automatic depth of field effect processing during self-photographing is achieved, and the self-photographing effect is better and more natural.

Description

technical field [0001] The invention relates to the technical field of photographing, in particular to a real-time depth-of-field method based on human faces. Background technique [0002] With the continuous improvement of living standards and technological levels, taking pictures has become a common behavior in our daily life. We can shoot the images we want at will to record memorable moments or scenes. In order to highlight the subject, the depth of field effect is usually used to make the subject clear and the background blurred, so that the subject can be separated from the background, making the subject more attractive, especially when taking selfies. However, the depth of field function needs the hardware support of the camera to support the depth of field when shooting. For ordinary shooting equipment, it is necessary to process the depth of field of the image after shooting. The operation is very troublesome, and it is a relatively difficult task for non-profession...

AI Technical Summary

Problems solved by technology

However, the depth of field function needs the hardware support of the camera to support the depth of field when shooting. For ordinary shooting equipment, it is necessary to process the depth of field of the image after shooting. The operation is very troublesome, and it is a relatively difficult task for non-professionals big problem

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