Title :
Enhancing the forensic value of handwriting using emotion prediction
Author :
Fairhurst, Michael ; Erbilek, Meryem ; Cheng Li
Author_Institution :
Sch. of Eng. & Digital Arts, Univ. of Kent, Canterbury, UK
Abstract :
Handwriting biometrics have a long history, especially when the handwritten signature is the target, but it has also proved possible to use handwriting as a basis for the prediction of various non-unique but forensically useful characteristics of the writer. Most commonly, these are socalled “soft biometric” characteristics such as the age or gender of the writer, but the predictive capabilities arising in handwriting offer wider opportunities for trait prediction. This paper presents a preliminary study of the use of handwriting to predict information about the writer relating specifically to higher level characteristics such as emotional state. We present some initial results to demonstrate that this is possible, and explore a number of particular factors relevant to the use of such a capability in areas of forensic investigation.
Keywords :
emotion recognition; handwriting recognition; image forensics; emotion prediction; handwriting biometrics; handwriting forensic value; handwritten signature; soft biometric characteristics; trait prediction; Accuracy; Biometrics (access control); Educational institutions; Feature extraction; Forensics; Stress; Writing; Handwriting analysis; trait prediction;
Conference_Titel :
Biometrics and Forensics (IWBF), 2014 International Workshop on
Conference_Location :
Valletta
DOI :
10.1109/IWBF.2014.6914248