A feature subtraction method for image based kinship verification under uncontrolled environments

摘要

The most fundamental problem of local feature based kinship verification methods is that a local feature can capture the variations of environmental conditions and the differences between two persons having a kin relation, which can significantly decrease the performance. To address this problem, we propose a feature subtraction method to remove the kinship unrelated part from the local feature through a linear function of which only one parameter, namely a subtraction matrix, needs to be inferred from training data. This is done by using a gradient descent method to simultaneously minimize the feature distance between face image pairs with kinship and maximize the distance between non-kinship pairs. Based on the subtracted feature, the verification is realized through a simple Gaussian based distance comparison method. Experiments on two public databases show that the feature subtraction method outperforms or is comparable to state-of-the-art kinship verification methods.