Video beautification system and method applied to Internet video live broadcast
An Internet video and video technology, applied in the field of video imaging, can solve the problems of poor visual perception effect of the face area and poor overall video effect, so as to improve the overall effect, improve detection accuracy and calculation speed, and achieve natural and comfortable visual perception Effect
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Embodiment 1
[0042] Embodiment 1: as figure 1 As shown, the first purpose of the present invention is to provide a video beautification system applied to Internet video live broadcast, including:
[0043] Beautification unit 1, camera 2, face detection library 3 and display unit 4; camera 1 is used to obtain video frames, and face detection library 3 is used to detect whether there is a human face area in the video frame, and when a human face area is detected, then Send a signal to the beautification unit; the face detection storehouse 2 is provided with a cascaded classifier, which is used to carry out pattern matching to the video frame, which improves the detection accuracy and computing speed; the display unit 4 is used to display the processing results of the beautification unit 1; the beautification Unit 1 is connected to camera 2, face detection library 3 and display unit 4 respectively. Beautification unit 1 includes filter module 1-1, brightness module 1-2 and contrast module 1-3...
Embodiment 2
[0044] Embodiment 2: as figure 2 As shown, the second purpose of the present invention is to provide a method for beautifying video applied to Internet video live broadcast, including:
[0045] ①. Initialization:
[0046] Set the radius r and threshold T of the fuzzy sampling area in the filtering module.
[0047] ②. The camera acquires the video frame I and transmits it to the beautification unit.
[0048] 3. The beautification unit calls the face detection library of OpenCV to detect the face area of the video frame I.
[0049]The full name of OpenCV is Open Source Computer Vision Library. OpenCV is a cross-platform computer vision library based on (open source) distributions that can run on Linux, Windows and Mac OS operating systems. OpenCV uses an integrated machine learning-based face detection algorithm originally proposed by Viola and Jones and improved by Rainer Lienhart. Based on haar-like features and Adaboost learning algorithm, the method classifies and tr...
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