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Robust Face Detection in Patient Triage Images

Disaster events like the attack on the World Trade Center in New York City in 2001 and the earthquake in Haiti in 2010 result in a desperate need for family and friends to obtain information about missing people. This can be facilitated by automatically extracting textual descriptors of patients from images taken at emergency triage centers. We show that existing face detection algorithms, a necessary precursor to extracting such descriptors, perform poorly on triage images taken during disaster simulations, and propose and demonstrate the superiority of an ensemble-based face detection method that is a combination of robust skin detection and simple pattern matching face detection techniques. The addition of a template-based eye detection method further improves the accuracy of our face detection method.