Along with the ever-growing Web

specified sensitive videos including horror videos and violent videos are disseminated over Internet and have threatened children's psychological health.It is necessary to effectively recognize and filter out these videos.So far

the existing recognition methods for specified sensitive videos either ignore the multiple contextual information among the shots

or ignore the dependent relationship among the multiple features.This paper presents a novel recognition method for specified sensitive video based on multi-context construction and linear fusion.First

multiple effective features are extracted and the multiple contextual structure graphs are constructed for the shots in one video clip.Then

a SVM classifier is trained using contextual information in each feature space.Finally

a linear dependency model is learnt to fuse multiple classifiers obtained in different feature spaces.Experiments on a specified sensitive video dataset demonstrate that the performance of our method is superior to the other existing algorithms.