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Visual roughened sensing for private human pose recognition

The rapid development of the Internet has made people increasingly dependent on networks for information transmission. Visual media such as digital images and videos have gradually become two of the most important forms of information exchange because they can be disseminated very quickly. However, images and videos often contain private data, such as corporate secrets and personal identity information and the harm caused by leakage of such data cannot be underestimated. Therefore, the security of images and videos has attracted widespread attention from the public and related researchers. At present, the processing of images and videos tends to include the following steps: sampling, compression, encryption, transmission, decryption, decompression, reconstruction, and intelligent processing. During these steps, images and videos are encrypted and decrypted by the sender and the receiver respectively to avoid potential leakage of private data by interception during online transmission. This processing mode is mainly aimed at preventing information-leakage problems during transmission, but it ignores the risks caused by the intelligent application of images and videos after their reconstruction. For the contradiction between existing data processing methods and actual social needs, a novel visual roughened sensing is proposed for typical intelligent applications such as private human pose recognition.