Video collection generation method and device, electronic equipment and storage medium
A collection and video technology, applied in the information field, can solve problems such as high technical requirements, low efficiency, inaccuracy, etc., to achieve the effect of reducing technical requirements, simplifying generation, and reducing manual errors
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example 1
[0203] This example provides a method for automatically generating video highlights, using football videos as an example for illustration but not limited to football videos. For example, in this example, a deep learning framework is used to solve the problem of automatically generating football video highlights. Through the powerful learning ability of the deep neural network, the video image and audio information are modeled separately. Use the text recognition function to detect the score position and real-time score in the game screen through statistical features, and output the score information. This example proposes a deep learning-based multimodal approach to more accurately locate highlights in football match videos.
[0204] A video collection for this example could include the following steps:
[0205] Step 1: Cut the video with the lens cutting method.
[0206] Step 2: Extract frames for each cut video (9 frames for each shot), and extract the audio of each video...
example 2
[0217] Such as Figure 5 As shown, this embodiment provides a method for generating video highlights, including:
[0218]Use the video lens cutting model to cut the video into separate shots; in some scenes, the shots are also numbered to mark the order of these separated shots in the video;
[0219] Extracting the image frames of the lens to obtain n image frames extracted, optionally, one lens contains more than n image frames;
[0220] Using the neural network to classify n image frames and averaging the classification results, the final image classification results are obtained based on the average;
[0221] From the perspective of image content, the primary classification result of shot classification is obtained based on the image classification result;
[0222] Extract the audio of each shot, and all the audio contained in a shot may include one or more audio frames;
[0223] Using convolutional neural network to classify audio, from the perspective of audio content,...
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