  Deaths and injuries are common in road accidents, violence, and natural
disaster. In such cases, one of the main tasks of responders is to retrieve the
identity of the victims to reunite families and ensure proper identification of
deceased/ injured individuals. Apart from this, identification of unidentified
dead bodies due to violence and accidents is crucial for the police
investigation. In the absence of identification cards, current practices for
this task include DNA profiling and dental profiling. Face is one of the most
commonly used and widely accepted biometric modalities for recognition.
However, face recognition is challenging in the presence of facial injuries
such as swelling, bruises, blood clots, laceration, and avulsion which affect
the features used in recognition. In this paper, for the first time, we address
the problem of injured face recognition and propose a novel Subclass
Contrastive Loss (SCL) for this task. A novel database, termed as Injured Face
(IF) database, is also created to instigate research in this direction.
Experimental analysis shows that the proposed loss function surpasses existing
algorithm for injured face recognition.
