Video semantic extraction method by combining object segmentation and feature weighing

The invention relates to a video semantic extraction method by combining object segmentation and feature weighing, which belongs to the technical field of video search. A video object semantic based on a background frame construction and a video semantic based on a key frame characteristic are classified for weighted calculation, i.e. respectively calculating the weighted sums of the classification results of the rapid robust features of a video object, the SURF features of a key frame, a color histogram, an edge histogram and local binary features corresponding to each semantic, and then comparing the weighted sums with a threshold to determine whether a semantic to be tested exists in a lens. Due to the adoption of background separation, the background noise is eliminated, and the accuracy of semantic classification is improved. Moreover, in view of errors and static video semantics possibly existing in video object extraction, a traditional method is used for classification. By combining the two methods, the accuracy of video semantic extraction is improved.