Abstract
| Language | Undefined |
|---|---|
| Place of Publication | Enschede |
| Publisher | Centre for Telematics and Information Technology (CTIT) |
| Number of pages | 9 |
| State | Published - Sep 2012 |
Publication series
| Name | CTIT Technical Report Series |
|---|---|
| Publisher | Centre for Telematics and Information Technology, University of Twente |
| No. | TR-CTIT-12-23 |
| ISSN (Print) | 1381-3625 |
Keywords
- forensic face recognition
- SCS-Safety
- METIS-289697
- IR-84357
- EWI-22268
- PIE $\cap$ MultiPIE problem
- fictitious forensic case
- PIE MultiPIE problem
Cite this
}
Database Cross Matching: A Novel Source of Fictitious Forensic Cases. / Dutta, A.; Veldhuis, Raymond N.J.; Spreeuwers, Lieuwe Jan.
Enschede : Centre for Telematics and Information Technology (CTIT), 2012. 9 p. (CTIT Technical Report Series; No. TR-CTIT-12-23).Research output: Book/Report › Report
TY - BOOK
T1 - Database Cross Matching: A Novel Source of Fictitious Forensic Cases
AU - Dutta,A.
AU - Veldhuis,Raymond N.J.
AU - Spreeuwers,Lieuwe Jan
PY - 2012/9
Y1 - 2012/9
N2 - Due to privacy concern and data protection laws, it is very difficult to obtain real forensic data for forensic face recognition research. In this paper, we introduce the concept of Database Cross Matching (DCM) as a novel source of fictitious but challenging forensic cases. DCM refers to the task of finding the subjects that are common in two different data sets. For most pairs of independent data sets, there will be no common subjects. However, for some data sets captured at the same institution, but independently and at different times, there is a high probability of finding some common subjects. We demonstrate the feasibility of DCM using the PIE and MultiPIE data set that were captured at the same institution in 2000 and 2004 respectively. We denote the task of finding the subjects that are common in PIE and MultiPIE data as PIE $\cap$ MultiPIE problem. Evaluation of the five face recognition systems applied to the PIE $\cap$ MultiPIE problem show that DCM can indeed create very challenging forensic problems.
AB - Due to privacy concern and data protection laws, it is very difficult to obtain real forensic data for forensic face recognition research. In this paper, we introduce the concept of Database Cross Matching (DCM) as a novel source of fictitious but challenging forensic cases. DCM refers to the task of finding the subjects that are common in two different data sets. For most pairs of independent data sets, there will be no common subjects. However, for some data sets captured at the same institution, but independently and at different times, there is a high probability of finding some common subjects. We demonstrate the feasibility of DCM using the PIE and MultiPIE data set that were captured at the same institution in 2000 and 2004 respectively. We denote the task of finding the subjects that are common in PIE and MultiPIE data as PIE $\cap$ MultiPIE problem. Evaluation of the five face recognition systems applied to the PIE $\cap$ MultiPIE problem show that DCM can indeed create very challenging forensic problems.
KW - forensic face recognition
KW - SCS-Safety
KW - METIS-289697
KW - IR-84357
KW - EWI-22268
KW - PIE $\cap$ MultiPIE problem
KW - fictitious forensic case
KW - PIE MultiPIE problem
M3 - Report
T3 - CTIT Technical Report Series
BT - Database Cross Matching: A Novel Source of Fictitious Forensic Cases
PB - Centre for Telematics and Information Technology (CTIT)
CY - Enschede
ER -