Abstract
In literature about selective encryption of image and video content, image quality indices are usually used to gauge the degree of encryption. These methods have frequently been shown not to work well for the evaluation of encryption, mainly due to them being trained on predominantly high quality contents. The problem for creating a proper recognition index or visual encryption strength index is the lack of data to train on. In this paper we present the first database of encrypted video content, ranging from high quality to completely unrecognizable, together with human observer scores for quality and recognizability. We also provide a basic evaluation of visual quality indices on this database, directly and in different combination by fusion, to showcase that currently image and video quality indices are ill fit for the purpose of estimating video encryption strength/recognizably. This inability of quality indices to perform also showcases that this database fills the required blind spot of currently available data.
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