학술논문

Pose Variability Compensation Using Projective Transformation for Forensic Face Recognition
Document Type
Conference
Source
2015 International Conference of the Biometrics Special Interest Group (BIOSIG) Biometrics Special Interest Group (BIOSIG), 2015 International Conference of the. :1-5 Sep, 2015
Subject
Computing and Processing
Engineering Profession
Photonics and Electrooptics
Signal Processing and Analysis
Face
Forensics
Face recognition
Cameras
Protocols
Databases
Manuals
Language
Abstract
The forensic scenario is a very challenging problem within the face recognition community. The verification problem in this case typically implies the comparison between a high quality controlled image against a low quality image extracted from a close circuit television (CCTV). One of the downsides that frequently presents this scenario is pose deviation since CCTV devices are usually placed in ceilings and the subject normally walks facing forward. This paper proves the value of the projective transformation as a simple tool to compensate the pose distortion present in surveillance images in forensic scenarios. We evaluate the influence of this projective transformation over a baseline system based on principal component analysis and support vector machines (PCA-SVM) for the SCface database. The application of this technique improves greatly the performance, being this improvement more striking with closer images. Results suggest the convenience of this transformation within the preprocessing stage of all CCTV images. The average relative improvement reached with this method is around 30% of EER.