Video quality evaluation method, device and apparatus and storage medium
A video quality and video technology, applied in video data retrieval, video data clustering/classification, television, etc., can solve problems such as simple, incapable of accurate and comprehensive description of video content, incapable of accurate evaluation of video quality, and achieve Improve timeliness and improve accuracy
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Embodiment 1
[0029] figure 1 It is a flow chart of the video quality assessment method in Embodiment 1 of the present invention. This embodiment is applicable to the situation of evaluating video quality. The method can be performed by video quality assessment. The video quality assessment device can be composed of hardware and / or software accomplish. The video quality evaluation device may be composed of two or more physical entities, or may be composed of one physical entity, and is generally integrated in computer equipment.
[0030] Specifically, such as figure 1 As shown, the video quality assessment method provided in this embodiment mainly includes the following steps:
[0031] S110. Decode the video to be evaluated to obtain image sequence and audio information.
[0032] It should be noted that the video server receives a large number of videos produced and uploaded by users every day. The server needs to eliminate illegal videos from all videos uploaded by users, and screen ou...
Embodiment 2
[0052] image 3 It is the flowchart of the video quality assessment method in the second embodiment of the present invention; this embodiment is applicable to the situation of evaluating video quality, and this embodiment further optimizes the video quality assessment method, such as image 3 As shown, the optimized video quality assessment method mainly includes the following steps:
[0053] S310. Decode the video to be evaluated to obtain image sequence and audio information.
[0054] S320. Using the motion feature extraction network to perform feature extraction on each frame of image to obtain a motion feature vector.
[0055] In this embodiment, before using the motion feature extraction network to perform feature extraction for each frame of image, it is necessary to build and train the motion feature extraction network. Further, building and training the action feature extraction network mainly includes the following steps: obtaining a set of training videos, and obta...
Embodiment 3
[0081] On the basis of the foregoing embodiments, this embodiment provides a preferred example. Figure 4 It is a flow chart of the video quality assessment method in Embodiment 3 of the present invention; as Figure 4 As shown, the above-mentioned video quality assessment method mainly includes the following steps:
[0082] S401. Obtain a video to be evaluated. The video to be evaluated may be a video just recorded by the user and uploaded to the server, or a video stored in the server without quality evaluation. Preferably, the video to be evaluated in this embodiment is preferably a short video recorded by a user.
[0083] S402. Decode the video to be evaluated to obtain an image sequence composed of multiple images arranged in a certain order.
[0084] S403. After the video to be evaluated is decoded, audio information of the video to be evaluated may be obtained. Audio information includes background music and language information of characters in the video to be eval...
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