Method for detecting specific contained semantics of video based on grouped multi-instance learning model

The invention relates to a method for detecting specific contained semantics of a video based on a grouped multi-instance learning model in the technical field of computer video treatment, which comprises the following steps: continuously cutting the video according to the shots, thereby acquiring a plurality of video segments; using a FFMPEG tool to intercept image describers for each video segment Sij, wherein averagely 25 pictures are intercepted from each video segment at the same interval; extracting the related audio describers by using a video audio track, intercepting the video describers by using a video screenshot set, and intercepting the motion degree by using the video; performing machine learning on each set of describers; and acquiring a result after performing the machine learning, performing an European distance calculation on the learning result and one describer of one target video, and using the acquired minimum value as the approaching degree of the original video under the description of