Abstract:
A method of reconstructing biometric face image templates of a face recognition system (FRS) using the match scores or distances provided by the FRS. The match scores represent the distance between a image introduced to the FRS and the unknown image template stored in the FRS. The present method uses an affine transformation approximating the unknown algorithm within the FRS and the match scores provided by the FRS to determine the coordinates of the unknown target template. The coordinates of the unknown target template are then applied to a pseudo-inversion of the affine transformation to produce a reconstructed image template of the unknown target. This reconstructed image template can then be used to ‘break-in’ to the FRS.
Abstract:
A system and method of automatically assessing pediatric and neonatal pain using facial expressions along with crying sounds, body movement, and vital signs change to improve the diagnosis and treatment of pain in the pediatric patient population.
Abstract:
A novel, linear modeling method to model a face recognition algorithm based on the match scores produced by the algorithm. Starting with a distance matrix representing the pair-wise match scores between face images, an iterative stress minimization algorithm is used to obtain an embedding of the distance matrix in a low-dimensional space. A linear transformation used to project new face images into the model space is divided into two sub-transformations: a rigid transformation of face images obtained through principal component analysis of face images and a non-rigid transformation responsible for preserving pair-wise distance relationships between face images. Also provided is a linear indexing method using the linear modeling method to perform the binning or algorithm-specific indexing task with little overhead.