Soft biometrics are a new form of biometric identification which use physical or behavioral traits that can be naturally described by humans. Unlike other biometric approaches, this allows identification based solely on verbal descriptions, bridging the semantic gap between biometrics and human description. To permit soft biometric identification the description must be accurate, yet conventional human descriptions comprising of absolute labels and estimations are often unreliable. A novel method of obtaining human descriptions will be introduced which utilizes comparative categorical labels to describe differences between subjects. This innovative approach has been shown to address many problems associated with absolute categorical labels-most critically, the descriptions contain more objective information and have increased discriminatory capabilities. Relative measurements of the subjects' traits can be inferred from comparative human descriptions using the Elo rating system. The resulting soft biometric signatures have been demonstrated to be robust and allow accurate recognition of subjects. Relative measurements can also be obtained from other forms of human representation. This is demonstrated using a support vector machine to determine relative measurements from gait biometric signatures-allowing retrieval of subjects from video footage by using human comparisons, bridging the semantic gap.

Soft biometrics is a new form of biometric identification which utilizes labeled physical or behavioral traits. Al though these traits intuitively have less discriminatory capability than mensurate approaches, they offer several ad vantages over traditional biometric techniques. Soft bio metric traits can be typically described as labels and measurements which can be understood by people, allowing retrieval and recognition based solely on human descriptions. Although being a key component of eyewitness evidence, conventional human descriptions can be considered to be unreliable. A novel method of obtaining human descriptions will be introduced which utilizes visual comparisons between subjects. The Elo rating system is used to infer relative measurements of subjects' traits based on the comparative human descriptions. This innovative approach to obtaining human descriptions has been shown to counter many problems associated with categorical (absolute) labels. The resulting soft biometric signatures have been demonstrated to be robust and allow accurate retrieval of subjects in video data and show that elapsed time can have little effect on comparative descriptions.