Joint inference of soft biometric features

Biometric and soft biometric features can be used to identify people in disaster situations, but the use of biometric features or pictures of victims may lead to privacy issues. Using text-based descriptors to describe disaster victim images would help in making person data public and also in searching for a particular person in a large database. In this paper, work on combining soft biometric features using a Markov network is presented. The proposed structure exploits the relationships between different soft biometric features and results into a robust text descriptor to help in identification of a person from a patient triage image. We show how interaction between individual feature detectors can lead to increased accuracy in the resulting text descriptor.