Title :
Metadata-based understanding of impostor pair score variations
Author :
Sgroi, Amanda ; Bowyer, Kevin ; Flynn, Patrick
Author_Institution :
Dept. of Comput. Sci. & Eng., Univ. of Notre Dame, Notre Dame, IN, USA
Abstract :
Metadata about a given face image can include information such as the subject´s year of birth, subject gender, and date of acquisition. By determining the degree of metadata matches between the gallery and probe images (such as two subjects having the same gender) we hypothesize that more metadata values that match for an impostor image pair increases the likelihood of a false match. In this work, we explore year of birth, gender, date of acquisition, and expression in an attempt to understand variations in match scores produced by impostor image pairs. Impostor pairs that fall in the weak partition as identified by the previously developed SNoW technique have a slightly larger number of matching metadata values. However, there is little to no statistically significant difference in the scores produced by image pairs with more matching metadata between strong and weak impostor pairs.
Keywords :
face recognition; image matching; meta data; SNoW technique; face image; impostor image pair; impostor pair score variation; matching metadata value; metadata matches; metadata-based understanding; probe images; Algorithm design and analysis; Face; Face recognition; Image recognition; Market research; Partitioning algorithms; Snow; biometrics; face recognition; metadata; score analysis;
Conference_Titel :
Information Forensics and Security (WIFS), 2014 IEEE International Workshop on
DOI :
10.1109/WIFS.2014.7084295