Semantic multimedia authentication with model vector signature

We propose novel techniques for image/video authentication at the semantic level. These methods use statistical learning, visual object segmentation and classification schemes for semantic understanding of visual content. A public digital signature, robust to rotation, scaling, and translation, is generated. The authentication process is executed by comparing the classification result with the information carried by the digital signature. This method leads the authentication system to learn the semantic content of multimedia data and to perform the authentication task at the semantic level.