Name
Abstract | ||
|---|---|---|
Soft biometric traits embedded in a face (e.g., gender and facial marks) are ancillary information and are not fully distinctive by themselves in face-recognition tasks. However, this information can be explicitly combined with face matching score to improve the overall face-recognition accuracy. Moreover, in certain application domains, e.g., visual surveillance, where a face image is occluded or is captured in off-frontal pose, soft biometric traits can provide even more valuable information for face matching or retrieval. Facial marks can also be useful to differentiate identical twins whose global facial appearances are very similar. The similarities found from soft biometrics can also be useful as a source of evidence in courts of law because they are more descriptive than the numerical matching scores generated by a traditional face matcher. We propose to utilize demographic information (e.g., gender and ethnicity) and facial marks (e.g., scars, moles, and freckles) for improving face image matching and retrieval performance. An automatic facial mark detection method has been developed that uses (1) the active appearance model for locating primary facial features (e.g., eyes, nose, and mouth), (2) the Laplacian-of-Gaussian blob detection, and (3) morphological operators. Experimental results based on the FERET database (426 images of 213 subjects) and two mugshot databases from the forensic domain (1225 images of 671 subjects and 10 000 images of 10 000 subjects, respectively) show that the use of soft biometric traits is able to improve the face-recognition performance of a state-of-the-art commercial matcher. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/TIFS.2010.2049842 | IEEE Transactions on Information Forensics and Security |
Keywords | Field | DocType |
facial mark detection method,feret database,image matching,face image matching score,face recognition,visual surveillance,numerical matching scores,face image,soft biometrics,visual databases,soft biometric traits,face matching,ancillary information,automatic facial mark detection,laplacian-of-gaussian blob detection,facial mark,face retrieval,biometrics (access control),traditional face matcher,image retrieval,global facial appearance,demographic information,soft biometric trait,morphological operators,primary facial feature,face recognition accuracy,face image matching,face marks,facial marks,active appearance model,face,biometrics,accuracy,databases,forensics,laplacian of gaussian | Facial recognition system,Computer vision,Soft biometrics,Pattern recognition,Computer science,Image retrieval,Active appearance model,Blob detection,Artificial intelligence,FERET database,Biometrics,Face detection | Journal |
Volume | Issue | ISSN |
5 | 3 | 1556-6013 |
Citations | PageRank | References |
77 | 2.80 | 19 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Unsang Park | 1 | 815 | 36.32 |
| Anil Jain | 2 | 33507 | 3334.84 |