Spontaneous expression classification in the encrypted domain
This addresses privacy concerns in facial expression analysis for remote clients, though it is incremental as it applies existing cryptographic methods to a new domain.
The paper tackled the problem of classifying spontaneous facial expressions while protecting subject identity by proposing a system that operates in the encrypted domain using Paillier cryptosystem with FLDA and kNN, achieving results on the NVIE database.
To date, most facial expression analysis have been based on posed image databases and is carried out without being able to protect the identity of the subjects whose expressions are being recognised. In this paper, we propose and implement a system for classifying facial expressions of images in the encrypted domain based on a Paillier cryptosystem implementation of Fisher Linear Discriminant Analysis and k-nearest neighbour (FLDA + kNN). We present results of experiments carried out on a recently developed natural visible and infrared facial expression (NVIE) database of spontaneous images. To the best of our knowledge, this is the first system that will allow the recog-nition of encrypted spontaneous facial expressions by a remote server on behalf of a client.