Video abstraction method based on progressive generative adversarial network

[0019] In this embodiment, a video summarization method based on a progressive generation confrontation network, such as figure 1 shown, including the following steps:

[0020] Step 1. Perform frame sampling on the abstract video at a fixed frequency, and divide the video into a collection of pictures frame by frame;

[0021] The video is composed of many pictures. The difference between several adjacent pictures is very small, and the information extracted from these pictures is basically the same. Therefore, the main information of the video is not only contained in one picture, but also in multiple adjacent pictures. It contains the main information of the video, and sampling the video at an appropriate frequency will not lose the content expression of the video. For a video R, the first image is f 1 , and then sample the video R at an interval I, and finally get pictures, the collection of these pictures F={f i , i∈[1, N]} can represent the main content contained in t...

[0037] In this embodiment, the following video is taken as the video to be summarized, and the video summarization method based on the progressive generation confrontation network of the present invention is used to summarize the video, wherein,

[0038] Video to be digested: A 2-megapixel surveillance video of an underground parking lot, which needs to be digested every 10 minutes for safety management or early warning.

[0039] Summary task: extract the key frames of the video, save the key frames of the video, and compress the length of the video.

[0040] Summary method:

[0041] Step 1. First, the video is frame-sampled at a frame rate of 10 frames per second (10fps), and the video R is divided into 6000 frames, that is, 6000 pictures. After segmentation, the video data is read as frame vectors and arranged in an orderly Reals, which is

[0042] Step 2. The video resolution of 2 million pixels is 1920*1080. Correspondingly, build a 9-layer progressive generation confr...