Reduction in Communication via Image Selection for Homomorphic Encryption-based Privacy-protected Person Re-identification

We propose a method for reducing the amount of communication by selecting pedestrian images for privacy-protected person re-identification. Recently, it has become necessary to pay attention to how features corresponding to personal information can be protected. Owing to homomorphic encryption, which enables a distance between features to be computed without decryption, our method can use a cloud server on a public network while protecting personal information. However, we must consider the problem of the large amount of communication that occurs between camera clients and the server when homomorphic encryption is used. Our method aims to reduce the amount of this communication by selecting appropriate pedestrian images using reference leg postures. In our experiment, we confirmed that the amount of communication dynamically reduces without significant degradation in the accuracy of privacy-protected person re-identification with homomorphic encryption.