Video beautification system and method applied to Internet video live broadcast
An Internet video and video technology, applied in the direction of instruments, character and pattern recognition, electrical components, etc., can solve the problems of poor visual perception in the face area and poor overall video effect, so as to improve the overall effect, improve detection accuracy and Calculation speed, skin improvement 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 library 2 is provided with a cascade classifier for pattern matching 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; filter module 1-1 receives fa...
Embodiment 2
[0044] Embodiment 2: as figure 2 As shown, the second object 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 OpenSourceComputerVisionLibrary. OpenCV is a cross-platform computer vision library based on (open source) distributions that can run on Linux, Windows and MacOS operating systems. OpenCV uses a face detection algorithm based on integrated machine learning originally proposed by Viola and Jones and improved by Rainer Lienhart. Based on haar-like features and Adaboost learning algorithm, the method classifies and trains...
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